Sales AI Tools

Wingmen is an agentic outreach product that reads buying signals every day, starts the conversation and follows up until there is a call on your calendar. It runs in a web app or straight from Claude with the Wingmen MCP, and it is built for founders, B2B teams and agencies. Instead of working from a list of job titles, Wingmen surfaces the moment someone needs what you sell, attaches the reason why, writes the opener from what that person actually said, and keeps following up across LinkedIn, email and voice notes on autopilot until a meeting is booked. The product is positioned explicitly against the "list of job titles" approach to prospecting. Wingmen's Lead Radar shows a daily set of signals — 24 signals, read for you every day — and each one carries a score and a one-sentence reason. In the illustrated feed, a founder who wrote "Three months of referrals, then nothing" appears as a pain-language post at 9/10; a founder coach who commented on a competitor's launch appears as a competitor engager at 7/10; a founder who posted about onboarding for fintech appears as a post author at 8/10; a new Head of Growth three weeks into the seat appears as a job change at 8/10; and a CEO hiring a first sales rep appears as a hiring post at 9/10. The point is timing: the moment someone needs what you sell, with the reason why. The largest group of signals Wingmen reads is posts and engagement. Pain-language posts catch people who wrote about the problem in their own words. Niche post engagers engage with posts about the space you work in, while topic post engagers engage with posts on the topics your buyer cares about. Competitor post engagers engage with a competitor's posts, and engagers on your posts liked or commented on what you posted. Wingmen also reads post authors — the person who wrote the post, not only the people reacting — and handles the company page to person case, where a company page posts the signal and Wingmen finds the person to write to. Event attendees cover who is going to the events your buyer goes to, and the follower pool covers people who follow you, or the voices your buyers listen to. A second group covers hiring and workforce movement. Hiring posts and job listings flag companies hiring for the problem you solve; job changes catch someone new in the seat, still making their first calls; companies hiring fast have many open roles at once, meaning the team is scaling; and growing teams show headcount climbing month over month. Company and market signals sit alongside these: website changes such as new pages, new pricing or a new product on their site; podcast mentions where they talked about the problem on a podcast; and news mentions of a launch, a press mention or a move that opens a need. Wingmen also reads advertising, technology, financial and regulatory signals. Companies running Google ads are spending on growth right now. Tech stack changes show a company that added or dropped a tool your product sits next to, and GitHub activity shows their engineers building in your space. On the financial side, funding posts indicate a company that just raised and has budget to spend, while Form D filings surface a fresh raise straight from SEC filings. When the day is quiet, cold search tops up the pipeline: cold search matches title and industry to your buyer, lookalike search finds people who look like your best-fit leads, and target accounts track movement at the accounts you name. Once a signal is caught, Wingmen runs a four-step sequence the site describes as "four wingmen, one booked call." Step one, the scout, spots the signal — a post about the problem, a new hire, a job change — the day it happens. Step two, the scorer, gives every lead a score and a reason in one sentence, and the opener is written from that reason, in your voice. Step three, the messenger, reaches out on LinkedIn first; if there is no reply, email or a voice note picks it up in the same sequence, on autopilot. Step four, the closer, brings replies into one inbox with an answer already drafted, and the meeting goes on your calendar. Wingmen can also be run from Claude. Connecting Wingmen to Claude as a custom connector lets you run outbound in plain words from the chat you already have open — asking for founders hiring their first sales rep returns leads the radar found that week, and a follow-up "yes, go" starts the agent on all of them. Two further capabilities extend outreach: voice notes are an add-on that lets you clone your voice once, after which Wingmen records a short note for each person based on their signal; and comment automations turn comments on your posts into conversations — someone comments the keyword, the DM goes out, and the thread joins your inbox. The stated outcome is a booked call rather than a list. Buyers are found daily, each with a written reason; outreach runs across LinkedIn, email and voice notes; every reply is read and sorted, ready to book; and every feature is included with no tiers, up to 600 leads a month per seat. Because the opener is written from the reason attached to the signal, the first message carries the context of what the person actually said or did instead of a generic pitch, and because the follow-up continues on autopilot across channels, a lead that does not answer on LinkedIn is still picked up by email or a voice note in the same sequence. Concrete scenarios follow directly from the signals the product reads. A seller watching for hiring signals can ask Wingmen for founders hiring their first sales rep and start the agent on everyone it found that week. A team can reach out to people who wrote about the problem in their own words, or to people engaging with a competitor's posts. A quiet day can be topped up with cold search, lookalike search or movement at named target accounts. Anyone who comments a keyword on your own posts can be turned into a DM conversation through comment automations, and voice notes let you add a personal spoken touch to each lead at volume. Wingmen is built for founders, B2B teams and agencies. The maker, Nemanja Milic, describes it as the agent he built because he sells without a sales team. Pricing is a single seat plan at $69 per month, discounted to $48.30 per month per seat with the PH30 code during the Product Hunt launch, at 30% off for life and valid until Dec 31. A 7-day free trial is available, and if you would rather have Wingmen run it for you, Concierge Outbound starts from $999/month. In short, Wingmen's value proposition is timing plus follow-through: it reads buying signals every day, explains why each lead matters, writes the opener from the signal itself, and keeps working the sequence across channels until a call appears on your calendar.

throxy is an outbound partner built for B2B companies selling into complex, hard-to-crack industries such as manufacturing, logistics, construction, education and healthcare — markets where generic outreach usually fails. Rather than handing you another dashboard, throxy builds prospect lists using custom, proprietary technology and then puts human sales development representatives on the phone and in the inbox to book qualified sales meetings on your behalf. The arrangement is simple on the buyer's side: you do not hire, ramp or manage anyone; you only choose which of the qualified meetings you want to take. throxy describes itself as Y Combinator's first AI-native sales agency and positions the service as a true outbound growth partner rather than just another sales platform, combining proprietary technology, data intelligence and human expertise. The stated purpose is to create a steady, predictable flow of high-value conversations with decision-makers in industries that are hard to reach but lucrative. The website is direct about the problem it addresses. Most tools, it says, overwhelm: they require tinkering, testing and fixing issues, and they lean on stale data or firmographic filters from generic data providers. Most agencies disappoint: they promise results but deliver poor leads, while SDRs are slow to ramp and need handholding. The industries throxy targets are described as complex, relationship-driven and full of noise — manufacturing is called one of the toughest markets to crack. Most outbound, the site argues, floods your calendar with noise, so the buyers actually worth your time get buried among unqualified conversations. throxy's answer is to combine its own outbound technology with a fully managed human team, so companies selling into traditional industries get real conversations instead of spam, and so internal sales teams can focus on what they do best: closing deals. The first pillar is custom lead targeting. Rather than renting access to a generic database, throxy builds tailored prospect databases from scratch based on your exact ideal customer profile. The site contrasts this with tools that rely on stale data or broad firmographic filters, and it emphasizes custom databases, niche-specific targeting and proprietary infrastructure that reaches buyers others cannot find. Lead research draws on scraped sources including LinkedIn, the prospect's website and Glassdoor, and it hunts for specific triggers — a recent fleet expansion, a new partnership — that make outreach timely. This matters in traditional industries where buyers are not searching for new vendors and where a well-chosen trigger is often the difference between a reply and silence. The second pillar is cold calling, powered by Maestro, the dialer throxy built itself to put SDRs on live conversations instead of dial tones. The site reports that the same team books twice the meetings on Maestro, with 121% more meetings booked per week since the dialer launched, 71% more meetings when calling is added, an 11% booking rate on calls lasting over two minutes, and zero people the customer needs to hire or train. A newer capability routes calls to an SDR who speaks the lead's language: a plant manager in Lyon hears French, a buyer in Munich hears German. The published interface shows an SDR note being written during a live call — qualified on production line downtime, interested in a Q3 pilot, asking about case studies in DACH, ready to book — illustrating how qualification happens inside the conversation rather than afterwards. The third pillar is qualification and approval. Every lead is qualified before it ever reaches your calendar against criteria the site lists as ICP (right company size), decision-maker confirmed, budget authority and timing confirmed, with leads failing a criterion marked to skip. Even after qualification, meetings go through a meeting approval step where you accept or skip each one, and throxy states plainly that it never books without your approval. A sample weekly calendar shows only the accepted names — a VP of Operations, a CEO, a CTO — reinforcing the promise that only qualified buyers make it through, with no noise and no wasted calls. The fourth pillar is messaging. throxy pairs email and cold calling end to end, using context-aware personalization drawn from scraped LinkedIn profiles and websites. The example on the site pairs a trigger observation ("Saw your recent Fleet expansion") with a website observation ("Congrats on your DHL partnership") before asking whether fleet expansion is relevant right now. Messaging-market fit is tested through A/B tests, such as Email version 1 versus a combined email and call sequence, and email deliverability is handled as a managed service, including warming email infrastructure during campaign buildout. The company lists its solution areas as lead finding and qualification, cold calling, messaging, deliverability and closed-loop optimisation, all delivered as a done-for-you service. How the whole thing runs is spelled out as a timeline. On days 1–2, throxy completes onboarding and strategy: ICP definition, qualification criteria and messaging frameworks are signed off, the team scrapes websites, LinkedIn and Glassdoor while searching for triggers, and briefs SDRs on value propositions and objections. On days 3–5 comes campaign buildout: the lead list is built and enriched, the SDR team is briefed and email infrastructure is warmed. From day 5 onward, calls and emails run in parallel, replies are managed and qualified leads are passed to you. From weeks 3–4 onwards, qualified meetings land on your calendar alongside weekly updates, A/B testing and continuous optimisation. The headline is that you are live within a week and see meetings within the month. The intended outcomes follow directly from that model. There are no dashboards to manage, no systems to learn and no resources to hire; the prospecting burden — finding targets, crafting personalised outreach, managing replies and booking meetings — is taken off your plate so your team can focus exclusively on closing. Because the system keeps testing and optimising, throxy says it learns and improves for your specific business the longer you work together. The result it promises is outbound sales that is predictable, profitable and painless, with a steady flow of high-value conversations in markets where outbound is hard, ignored or broken. Concrete scenarios appear throughout the site. A manufacturing software company describes throxy as more than a tool and a true outbound partner, starting real conversations rather than sending spam so the sales team can concentrate on closing. An education solutions provider credits personalised outbound with putting the right message in front of every educator at the perfect moment, unlocking qualified opportunities and freeing time for customers. A third customer reports 12 meetings in 20 days in December — described as the toughest month for outbound — and 137 meetings booked by July 2026 with an 80% show rate. The site also illustrates trigger-driven work with a mid-market logistics ICP: Director of Operations persona, fleet expansion trigger, and outreach referencing a DHL partnership. throxy is aimed at B2B companies selling into traditional, complex or niche industries — manufacturing, logistics, construction, education and healthcare are all named — including teams that have been burned by generic data providers or agencies delivering poor leads. Both email and cold calling are fully managed, and all SDRs are humans. On commercial terms, throxy states that you pay for meetings you accept that actually happen, which shifts the cost toward delivered pipeline rather than effort. The site does not publish tiers or list prices; instead it routes prospects to a strategy call booking form, and its FAQ addresses setup requirements, cold calling, using your own CRM or pipeline tools, niche industries, time to first meetings and how the service differs from a traditional lead gen agency. The takeaway is that throxy sells outcomes rather than software: proprietary list-building technology plus a human SDR team running email and multilingual cold calling, with qualification and approval gates so only meetings worth your time reach your calendar. For companies in hard-to-crack industries, the value proposition is pipeline delivered without hiring, ramping or managing anyone — and paying only for meetings you accept that actually happen.

Papermark Data Rooms is a virtual data room built for sharing sensitive documents during diligence and transactions. According to the company's own description, it brings granular access, dynamic watermarking, a Q&A module and a full audit trail into one place, and a room can be launched in under 60 seconds. The product is aimed at teams handling fundraising, mergers and acquisitions, due diligence and investor relations — anyone who needs to give investors, buyers or partners access to confidential material without losing control over who sees what, when they see it, and how they interact with it. Papermark describes a data room as a secure online repository, a kind of digital filing cabinet that replaces emailed PDFs with a single link carrying granular access controls and real-time activity tracking. The problem Papermark addresses is familiar to anyone who has run a deal: documents get emailed as PDFs, lost, or forwarded without permission, and there is no reliable view of who read what. Papermark's site frames data rooms as essential for businesses navigating fundraising, M&A, due diligence or strategic partnerships, because they streamline document sharing, protect intellectual property and demonstrate a professionalism that builds trust. Where a pile of attachments creates back-and-forth communication and slows decisions, a well-organized data room is presented as a way to accelerate decision-making and reduce that back-and-forth. Papermark also positions its approach as combining robust security with simplicity, and it notes that it started as an open source and self-hosted solution — a background it says shaped its focus on absolute control over data. Granular permissions are the center of the product. Within a single data room, administrators can create viewer groups and assign access at file level or folder level, so different investors, buyers or partners see only the documents meant for them. Access controls are complemented by an allow list and email verification, which let teams control access by email domain, and by custom link permissions covering expiry dates, password protection and email verification. Teams can send email invitations and new document notifications, and viewer activity is tracked through an audit log. A one-click NDA and agreements feature makes it possible to require viewers to accept an NDA before they gain access, and NDA-before-viewing appears alongside allow lists and screenshot protection in the feature list. Document protection features are designed for high-stakes sharing. Dynamic watermarking adds viewer details and custom text to documents, and screenshot protection blurs content when a screen capture is attempted — both listed under how Papermark protects against unauthorized sharing. Redaction lets teams black out text and images before sharing, while the separate AI redaction capability detects PII and custom terms, routes them to a review workspace, and then burns the redactions in. Underneath these features sits the security posture: SOC 2 Type II and ISO 27001 certification, GDPR and CCPA compliance, HIPAA compliance for healthcare data, AES-256 encryption described as military-grade, 2FA and SSO for advanced user authentication, and a choice of data residency across EU, US and UAE data centers, with more than 38 data centers listed. Analytics in Papermark are page-level rather than only document-level. The company says you can share a data room from a link but still track activity on each document inside the room and on each page within that document, showing exactly who is engaging with which material. The Q&A module adds structured communication: buyer or investor questions are routed and answered inside the data room with custom permissions, so conversations stay attached to the deal instead of scattering across email threads. Automatic file indexing means uploaded files are indexed for search, which helps viewers find material inside a room that may contain many documents and folders. Setup is deliberately lightweight. Documents and folders are uploaded through a drag and drop editor with bulk actions and support for large files, and the company advertises unlimited data rooms, unlimited visitors with no per-viewer charge on any plan, and unlimited storage and documents. Each room can carry custom branding with the customer's logo and colors, and custom domains let the room be shared on the customer's own domain. Fully white-labelled rooms are available as a plan feature, and the site's headline promise is white-labelling on your domain with clear data room pricing. Papermark says you can share a branded data room via a link and customize the design of each room, which matters when the room is often the first impression a counterparty gets of the business. The newest angle is agent-driven data rooms. Papermark describes Data Rooms 2.0 as secure data rooms your AI agents can run, live in under 60 seconds, and it exposes the product through an API, a CLI and an MCP server that together provide 57 operations for programmatic data rooms. Workflows automate recurring data room steps. The practical effect, as described, is that a team can create and manage rooms from a script or an agent rather than only through the web interface, while still using the same permissions, audit logging, analytics and Q&A. Multiple teams can be created and managed in one account, and enterprise buyers can request custom deployment, security review and procurement support along with SSO and a dedicated support team. A dedicated account manager is listed for deal teams on higher plans. The stated benefits are control and speed. Instead of emailing PDFs that may be lost or forwarded, teams share one link with granular access controls and real-time activity tracking, and the audit log and page-level analytics tell them who engaged and where. Protection features such as watermarking, screenshot protection, NDAs and redaction reduce the risk of leaks and unauthorized sharing, while certifications and encryption address the security review that enterprise counterparties tend to run. Papermark cites customer outcomes: Backtrace Capital says it raises a €50M+ Fund I using Papermark Data Rooms, and another customer says the team saved 70% and scaled sales and fundraising with a modern data room. The company also points to speed of setup, launching a room in under 60 seconds, and reports that 70,000 companies trust Papermark Data Rooms for deal flow. Use cases named on the site include fundraising, where teams share financials, cap tables and pitch decks with potential investors; M&A, to facilitate secure due diligence during mergers or acquisitions; partnerships, to provide secure access to relevant documents while protecting IP; and investor relations, to keep board members and investors informed with organized documents. Customer stories add portfolio management and portfolio updates, where updates and reporting are centralized; project management, where teams collaborate and manage projects transparently; marketing and prospecting, where marketing materials are shared and engagement with prospects is tracked; sales and sharing proposals, where proposals are shared and client engagement tracked; raising a fund; due diligence for transactions; and startup fundraising at every stage. Dedicated data room examples cover real estate, investment banking, due diligence, sales and startups. On pricing, Papermark publishes plan tiers — DataRooms, DataRooms Plus, DataRooms Premium and DataRooms Unlimited — with 3, 5, 10 and unlimited team seats respectively, noting that extra users are billed per seat. Unlimited data room visitors, unlimited data rooms and unlimited storage and documents are listed across plans, and a 7-day free trial is offered alongside a book-a-demo option. Beyond the plans sit Papermark Enterprise, with custom deployment, security review and procurement, SSO and a dedicated support team, and a self-hosted version that runs Papermark on your own infrastructure under the open-source licence with your own S3-compatible bucket. Taken together, Papermark Data Rooms is positioned as a modern, security-first data room for deal teams: fast to launch, controlled down to the file, folder and page, protected by watermarking, NDAs, redaction and encryption, measurable through page-level analytics and audit logs, brandable on your own domain, and now operable by agents through the API, CLI and MCP server.

MyLens is an AI workspace for delivering one-on-one presentations at scale. Rather than building a deck once and repeating the same walkthrough for every person, you upload your raw sources — documents, notes, recordings and more — say what matters, and invite your audience list. MyLens AI then gives every individual a live, private presentation generated from your material, answers their questions using those same sources, and reports back to you on how each session went. The product is built for anyone who explains the same thing to many people: sales teams, customer success, people and HR, founders, educators and trainers, and leaders. Its promise is simple: let every person feel presented to, one on one. The problem MyLens addresses is stated plainly on its own site: you can't present 1-1 to everyone. The best way to share something important is one-on-one — tailored slides, a live walkthrough and answers to each person's specific questions — but that takes hours per person, and it is impossible to scale by hand. MyLens does the math for you: presenting to 24 people at 30 minutes each is 12 hours of your time. With MyLens, the same audience is covered by about 20 minutes of setup, once, after which every person gets their own private personal presentation. The company frames this as going from one person to a thousand, with each person still receiving a private, personalized session rather than a broadcast. Setup starts with what you already have; no deck is needed. You drop in docs, notes and recordings — the site lists PDF, long text, Word, slides, YouTube, website, Markdown, audio, image, spreadsheet, Google Drive and ChatGPT output as accepted source types — and MyLens AI turns them into a clear, visual presentation. Alongside sources there is a Knowledge layer where you define the goal and tone, the audience overview, and what the AI should never say. In the product's own example, a pricing memo becomes a presentation built for each person, and an onboarding goal (get new hires productive in their first 30 days) with an audience of new engineers and their managers shapes how the material is framed. The presentation itself is delivered live and one-to-one. Everyone opens a private link and enters the six-digit code from their invite, and MyLens presents to them whenever they are ready — each visual is explained, and the session runs as a conversation rather than a recording. During the session people can stop and ask anything in their own words, right on the slide. MyLens answers from your sources and, when words are not enough, creates a new visual or a new layer in real time. The site's example shows an audience member asking what a contributor actually gets access to, followed by a drill-down infographic on code repositories — contributor or developer access, version control and peer pull requests, provisioned by the engineering lead — generated for that specific question. Because the AI is presenting on your behalf, MyLens puts explicit controls around what it may do during a live session. You choose whether the AI can create a new slide, drill down into more detail, and cite sources, so the boundaries of each session are set before anyone joins. On the audience side, you invite people into private sessions and track them through clear statuses — invited, opened, presented, asking a question, and follow up — so you can see at a glance who is presenting right now and who needs attention afterwards. The overall workflow is laid out as six steps: add your sources, teach your AI, let the AI create your presentation, choose what the AI may do, invite your audience, and go live. That sequence is the product's core methodology — set it up once and the AI presenter handles the rest, running every session in parallel rather than one after another. The site illustrates the scale visually: a single presenter on one side, and on the other an AI presenter running 1,000 people and 1,000 sessions at the same time, with individuals shown as presented, presenting now, asking a question, opened, or invited. Afterwards you see how each session went. You can review every audience session individually — time spent, questions asked and who needs a follow-up — for each person, with a per-person row showing name, role, status, session date, duration and session code, plus aggregate numbers such as invited, opened, presented and total time. That reporting closes the loop on a one-to-many presentation: instead of guessing whether the message landed, you can see who is doing well, who is stuck, and what to do next for every individual on the list. Trust is a stated design principle. MyLens says the AI only says what you would say: every answer comes from the files you added, and if the answer isn't there it says so and flags it for you. Every session is private — one person, one code, one conversation — so audience members do not sit in on each other's presentations. On data, the site states that what you bring stays yours: content is never used to train AI models, files are private by default and only your workspace can open them, data is encrypted, and you can delete it whenever you want. The site names six groups it is built for, each with a concrete scenario. Sales teams give every prospect a personal walkthrough of the offer. Customer success explains renewals and updates to each account, one by one. People and HR welcome every new hire with the same careful onboarding. Founders send each investor a private update they can question. Educators and trainers run lessons that answer back at each learner's own pace. Leaders explain a big change to every person, privately. In each case the same body of source material is reused, but the session adapts to the individual on the other side of the link. MyLens works with the AI you already use. You can do research in ChatGPT, Claude, Cursor or your own agents and send it to MyLens over MCP, where it becomes a presentation each person gets one on one. The listed connections are ChatGPT, Claude, Cursor, your own agents and MCP servers, so material produced elsewhere can be turned into private live sessions without rebuilding it by hand. In short, MyLens replaces the unscalable one-on-one walkthrough with an AI presenter that runs a private, personalized live session for every person on your list, grounded strictly in your sources, controllable down to what the AI is allowed to do, and measurable afterwards through per-person session reporting. Your first presentation is ready in minutes, and the value proposition stays the same whether you are presenting to a few people or to a thousand: let every person feel presented to.

sellphotos.online is an online store for your shoots, built for event photographers, schools, colleges and sports clubs.How it works:Upload an event shoot. The previews get your watermark (27 designs, with your text or logo); the originals stay private.Share one link or a print-ready QR code. Guests open it on any phone, with no app and no sign-up to browse.A guest takes a selfie and face search shows only the photos they're in, out of hundreds or thousands.The guest pays you directly, the way you already get paid (UPI, bank transfer, or anything you write as your payment details), and uploads a payment screenshot.You check the money arrived and approve, the watermark comes off, and the guest downloads the full-size originals.The money never passes through the platform, so there's no commission, no payout fee and no identity checks to open a store. You pay one yearly plan, from $99, sized by how many photos you upload and how many orders you approve.Pricing that sells more: per photo, "all my photos" and whole-event prices, volume discounts, and any of 47 currencies. Every order step is emailed to the buyer with your reply address, and unpaid orders get reminders.Privacy: the selfie image is never stored. It's matched only against that event's watermarked previews, the result expires after 24 hours, and you can turn face search off per event.

Pancake is a go-to-market platform that its makers describe as "The Vercel for GTM." The product gives your agent the brain, the data and the tools to run your go-to-market, and it is pitched at teams who want to deploy GTM ideas that bring in customers rather than build more software. It provides the building blocks to deploy any go-to-market idea from a favourite AI agent such as Claude or Codex: a GTM Brain, sending infrastructure, and data providers and enrichment, all accessible through one MCP connection. The core promise is simple — one prompt in, leads keep coming. You type a GTM idea, Pancake builds the Play, and one click deploys it. The positioning starts from a specific observation carried on the site: building got 10x easier, but selling didn't. While shipping software has become faster and cheaper, the work of actually finding and winning customers has not kept pace. Pancake's answer is to treat go-to-market as something you deploy rather than something you grind through manually. Instead of stitching together research tabs, spreadsheets, enrichment tools and an outreach sequencer by hand, Pancake packages the whole motion — who to target, where to find them, what to say and how to follow up — into reusable, running Plays. The result is a system that keeps searching for people who fit rather than a one-off list you exhaust in a week. The first step is the GTM Brain. You add your website and Pancake builds the Brain from it: from your website, Pancake learns who buys from you, what to say, and where to find them, and the site states that this stays always up to date. The Brain covers competitors, ICPs, outreach, influencers, market research and a market profile. That research profile includes details such as the company, its offering and its ideal clients — for example "websites for startups" and "funded B2B startups." Because everything downstream reads from the Brain, outreach and targeting stay consistent with how the company actually positions itself. It is the brain that the rest of the product draws on when it reads your Brain and your Plays to decide what a good lead looks like. The second step is the Play. A Play is one GTM idea put to work: it keeps searching for people who fit. You say who you want and Pancake builds the Play for you; you can start one in Pancake, in Claude or in Codex. A Play is defined by a handful of parts: who you are looking for, the signal that qualifies them, how many you want, and when it runs. In the demo, that looks like founders and heads of marketing at B2B startups of 10 to 50 people, with the signals "seed round" and "hiring marketing," running daily at 25 leads a week. Pancake also offers suggested Plays as starting points, such as "Funding — just raised a round," "Hiring — hiring a marketing lead," and "Keyword — posting about a rebrand." Building a Play is free, so teams can try any GTM idea without committing. Plays are powered by data sources you can trust. Pancake reads funding rounds, open roles and tech stacks from providers such as Dealroom, TheirStack, Wappalyzer, Apify, Firecrawl and Coresignal, and the page notes 30+ data providers (the Product Hunt description cites 40+ data providers and enrichment). Every lead shows why it fits and where that came from — a lead card can include the person's role, company, industry, location, seniority, and a "why they fit" line such as "Quillfern raised a seed round this month and is hiring a marketing lead." Leads can be added to a sequence or marked "not a fit." Because the sourcing is evidence-based, the person reviewing a lead can see the signal behind it rather than trusting an opaque score. Once leads are approved, Pancake handles the outreach. It writes a personal message for every lead, opening with their signal — a post, an open role, a funding round — and each sequence has its own language and tone. Drafts can be edited before they send, and messages go out in your voice under your name. You approve every lead before anyone is contacted. Pancake then follows up until they answer and reads the reply; a yes gets your calendar link, sent from your account, while every other answer comes back to you. The product's stated goal at that stage is that Pancake gets you the meeting and you close it. Pancake's distinctive approach is that the whole system is exposed to an AI agent. Connect Pancake to Claude or Codex with a browser sign-in, and you can build Plays, review leads and edit messages from the chat you already use. The same request works from Claude or Codex through Pancake's MCP server — "Set up Pancake by reading https://pancake.ai/install.md and following its instructions." In the demos shown on the site, the agent reads the GTM Brain, searches funding news and hiring data through Pancake, and then asks permission to use a tool such as "Deploy Play" or "Approve leads." Pancake is therefore both an app and a set of tools an agent can call. Pancake also learns from what wins. Approving or rejecting a lead teaches the Brain who fits, and each Play tracks contacts, replies and wins so you can see what works. The site shows this as a "what worked" panel — for example leading with the seed round, shorter intros, and asking for Thursdays — followed by "Brain updated." Reported outcomes from users include $50K of pipeline in 7 days, a 10%+ reply rate, and 15 meetings booked in a week, alongside a reply rate improvement of 56% versus the previous period. Practically, that means less time spent rebuilding lists and more time spent in the conversations that turn into revenue. Pancake is aimed at founders, marketing leads and go-to-market teams at B2B startups — the same kinds of people the Plays are built to find — as well as teams that already work inside Claude or Codex. The site lists customers and supporters including Kong, Hyperspell, AgentMail, Fleet, Requesty, Alpic, Praxis, Kinro, Vector Legal, Covera, Spacefill and Kardinal. Pricing starts from $99 a month per workspace with your whole team included, built to land 2 to 3 customers a month. That plan includes 60,000 credits a month with every lead checked against your ICP, unused credits rolling over in a slow month, free Play building, a personal message for each lead in your voice, and approval of every lead before anyone is contacted. A free start includes 15,000 free credits valid for 7 days, and you can also book a demo. In short, Pancake packages go-to-market into deployable units. It builds a GTM Brain from your website, turns a single prompt into a Play that keeps sourcing qualified leads, writes and follows up in your voice, and lets you run the whole thing from Pancake, Claude or Codex. For teams that have found building easy and selling hard, it is a way to treat customer acquisition as infrastructure you deploy rather than a manual chore you repeat.

Agent Craft is a team social media system that turns a company's employees into a coordinated content engine. Instead of asking marketers to write posts for a single company page, Agent Craft has each team member answer a daily prompt in a mobile app with a short voice note or video of about three minutes. The product then handles the formatting, narration, logo and URL placement, hashtags, classification, analysis and adaptation to each platform's best practices, and publishes the results across eight social platforms from each person's own account. A single web dashboard at app.agentcraft.ai collects everything for review, so nothing goes out unseen. Agent Craft is built on a simple observation stated on its site: people follow people, not logos. The same message delivered from a real team member's account earns roughly seven times the engagement of a company page post, because customers get to know the humans behind the business and trust follows. A company page today is one account with one voice — a logo avatar and a marketing voice — which the site describes as a 1× baseline. Real numbers published by Agent Craft from its own three-person team show the gap in practice: over the 30 days to September 13, 2026, exposure reached 234.1K, up 183% on 82.7K in the previous 30 days; engagements hit 13.3K, up 377% on 2.8K, including 10.4K likes, 1.8K comments, 854 shares and 225 saves; the engagement rate reached 5.7%, up 2.3 points from 3.4%; and 285 posts were published, up 115 on 170, across 26 active days at 11.0 posts a day with a longest gap of two days. The starting point is the Agent Craft mobile app. Every team member receives one prompt a day — a question about their work, a customer, or the week's news — and the prompts are tied to your campaigns so the whole team stays on message. The site gives an example prompt: "What's one thing a customer taught you this week?" The person answers by talking rather than typing, the way they would explain it to a colleague, with no scripts and no editing. A recording takes about three minutes, after which it flows automatically to the dashboard for review. Agent Craft states that team members do not need to be marketers: if someone can talk for three minutes about their work, they can use the product, which was built for teams where the people with the most expertise have the least time to write. Once a recording lands, Agent Craft runs the "Craft" step. The system handles formatting, narration, the placement of your logo and URL, hashtags, classification, analysis, and adaptation to each platform's best practices, producing platform-native versions of the content in the speaker's own voice. Agent Craft describes the flow as three steps: record a short voice note or video in the app about a customer story, a lesson or a take on the news; let Craft handle formatting, narration, brand assets, hashtags and platform-native versions; then review and publish through a single queue — one approval covering eight platforms. The eight platforms named across the site are LinkedIn, TikTok, YouTube, Instagram, Facebook, X (Twitter), Threads and Bluesky. All team content flows through one unified web dashboard where it is approved, edited and kept on brand before it posts. Three capabilities are called out. Approve means one queue for the whole team, so nothing ships unseen. Edit means any post can be refined before it goes out, per platform. Stay on brand means templates put your visuals, logo and URL on every post. Because the queue is shared, managers always know what is going out, from everyone, everywhere. The summary the product uses for the workflow is "3 min a day, 8 platforms, 1–1,000 teammates, 1 review queue." Agent Craft's methodology is captured in its "math" section: 7× engagement × 8 different platforms × number of team members = 100× the engagement you currently get from social media. The site breaks that down step by step — a company page today is one account with one voice at 1×; one teammate's account, because people follow people, performs at 7×; distributing that across eight platforms where each post is adapted natively reaches 56×; and putting the whole team to work in unison takes it to 100×. Coordinated campaigns are what hold it together: a promotion, a customer win or industry news goes out across the team in the same week, with each post delivered in that individual's own voice, while custom templates close every post with brand visuals, logo and URL. The outcomes Agent Craft publishes are engagement, reach, follower growth and qualified pipeline. Case studies on the site include Dr. Dominick Gadaleta, a facial plastic surgeon, with +644% and 73.3K impressions in 30 days, a 6% engagement rate that the site calls twice the industry standard, and 13.9% follower growth (+2,561 in 30 days). Mindset AI, a B2B AI SaaS company, recorded +296% and 148.9K impressions in 30 days, a 5.4% engagement rate described as almost twice industry standard, and 1.5% follower growth (+611 in 30 days). Juan Mouton, a fractional CMO, saw 41.3K views in 15 days, a 2.2% engagement rate and 2 new clients in 15 days. Agent Craft's own accounts reported 326.4K impressions in 90 days, reach +812% and a 5.1% engagement rate, and the site notes that many of its earliest users started brand-new accounts and began posting immediately on sign-up. On the lead side, Agent Craft moves "from engagement to pipeline." Hundreds of thousands of engagements generate hundreds of comments and DMs, and Craft reads every one across every teammate and all eight platforms. It captures each comment and DM, automatically qualifies buying intent and separates it from noise while keeping the context of what the person engaged with, and pushes qualified leads to your CRM where the sales team already works. The site illustrates this with an example inbox: a comment from a 40-person sales team asking how onboarding works, a DM from someone looking to replace their agency by Q1, and more than 412 further engagements in a week, with the buyer-intent messages surfaced as hot leads. The stated goal is that reps focus on the conversations that matter instead of sorting through everything manually. Agent Craft is designed for teams that want many voices rather than one, and the dashboard supports from a team of 1 to a team of 1,000. Published examples include a solo facial plastic surgeon, a B2B AI SaaS company, a fractional CMO, and a startup posting around a Product Hunt launch. Pricing is $95/month for the first teammate and $75/month for each additional teammate, and the plan is stated to include everything: unlimited recordings, 8 platforms, custom brand templates, analytics and dedicated onboarding. A 30-day free trial is available with no card needed, and teams can also book a 20-minute demo in which Agent Craft maps the first week of coordinated posts. Comment and DM data is pushed to the CRM the sales team already uses, and the mobile app handles recording while the web dashboard handles review and publishing. Agent Craft's core promise is that three minutes a day per person, multiplied across a whole team and eight platforms, produces engagement and leads that a single company page cannot. It removes the two biggest obstacles to consistent social posting — deciding what to say and doing the production work — by prompting each teammate for a spoken answer and handling everything from narration and brand templates to platform-native formatting, review and publishing. The result is coordination without scripts, brand consistency without bottlenecks, and a flow of qualified conversations moving from social engagement into the CRM.

SalesRep is an all-in-one omnichannel customer communication platform built around a single, AI-powered team inbox. It unifies every customer channel, CRM and AI provider in one place so teams can capture leads, automate conversations, broadcast campaigns and close deals faster from a single platform. The product also acts as a virtual sales rep that sells for you 24/7: it pulls live prices and stock from Shopify, WooCommerce, PrestaShop, Meta Catalog or your own database and API, answers customers on WhatsApp, Instagram, Messenger, email, SMS and other channels, and sends product cards and quotes on the fly in any channel. SalesRep follows up automatically until the deal closes, allows human takeover at any time, and works in more than 30 languages that are auto-detected. It is used by more than 1,000 businesses worldwide. As chats and calls multiply, old inboxes and workflows break. Teams that sell and support customers across WhatsApp, Instagram, Messenger, email, SMS, voice and social media end up juggling multiple platforms, losing context and leaving conversations unanswered. SalesRep addresses this fragmentation by giving every customer one reliable record and every conversation one thread, no matter which channel it came from. Instead of silos, the platform offers a unified conversation history, automatic contact merging and deduplication, real-time sync with your CRM, and smart routing based on channel and context. The stated goal is to help businesses manage the entire customer journey in one place, even at high volume — a framework SalesRep calls Conversation-Led Growth. At the centre of SalesRep is the Omnichannel Team Inbox. It unifies contacts from voice calls, email, WhatsApp, TikTok, Facebook Messenger, Instagram, Telegram, SMS, WeChat, MS Teams, Slack, iMessage, Google Business and more, including Asterisk. Every conversation appears in a single thread and every customer in one place, so agents no longer switch between apps or maintain separate inboxes. The inbox includes unified conversation history across all channels, automatic contact merging and deduplication, real-time sync with your CRM (or SalesRep's own CRM), and smart routing based on channel and context. SalesRep states that chat channels deliver 92%+ open rates, and that messaging channels support product catalogs and in-chat payments. The inbox also supports team and custom inboxes, live chat and popup widgets, a knowledge base and canned responses, mobile app access with 2FA, and AI call and chat summaries. SalesRep's AI Agents are AI that sells, supports and scales. Ready-made or custom agents qualify leads, answer FAQs, recommend products, book appointments, route enquiries and handle support requests around the clock, across every messaging channel. The site reports that 75% of chats are handled entirely by AI and 80% of conversations are resolved by AI. Agents perform multimodal processing — text, images, audio and files — so they can send documents and images and process screenshots, audio and files for full context understanding. AI sales automation sends product offers with photos, prices and live stock in real time, answers voice messages with its own voice replies, auto-detects each customer's language and replies in it, generates and sends quotes instantly without human intervention, follows up automatically on every quote until it closes, and hands the conversation to your team whenever needed. Additional AI Agent capabilities round out the offering. Guardrails define what AI Agents say and do so they stay on-brand and compliant, and humans can take over active conversations instantly. A RAG-powered knowledge base lets agents pull verified answers from knowledge sources such as PDFs, doc files, catalogs, images and websites, continuously updated for accuracy. Voice AI provides natural, human-like speech. Agent specialization lets you orchestrate teams of micro-agents focused on tasks like retrieval, routing and escalation for precision results at scale. Teams can start quickly with ready-made AI Agent templates or build a fully customized agent tailored to their business needs and workflows. Agents also collect data, update lifecycle stages, resolve support issues, recommend products, share images and trigger workflows automatically. Beyond the inbox and agents, SalesRep provides AI Workflows and Broadcast campaigns. Workflows let teams build powerful automations with a visual drag-and-drop builder to automate repetitive tasks, sync data across platforms and keep the team focused on closing deals rather than manual busywork, with automatic lead routing and assignment, real-time CRM sync and custom field mapping. Broadcast lets you send targeted messages across WhatsApp, SMS, Facebook, Instagram, Telegram and Email in one click, sharing promotions, product updates and newsletters directly to the channels your customers use most. Broadcast features include multi-channel campaigns, audience segmentation and targeting, delivery and engagement analytics, and automated opt-in/opt-out management. SalesRep connects to HubSpot, Salesforce, Jira, Zapier and 40+ tools, plus Shopify, WooCommerce and PrestaShop. SalesRep's overall approach is organised around its Conversation-Led Growth framework, which is designed to help businesses manage the entire customer journey across every channel in one place, even at high volume. The platform describes three pillars. The first is the Omnichannel Team Inbox, which unifies contacts from voice, email, WhatsApp, TikTok, Facebook Messenger, Instagram and more into one thread per customer. The second is AI Agents, which answer FAQs, qualify leads, route enquiries, book appointments and handle support requests around the clock. The third is Automate & Integrate, which connects SalesRep to HubSpot, Salesforce, Jira, Zapier and 40+ tools to automate workflows, sync data and eliminate manual busywork. A published sample conversation shows an AI agent greeting a customer, quoting an IP phone with a reference, price and live stock, preparing a quote for four units, sending a PDF quote by WhatsApp and email, and scheduling an automatic follow-up. The site publishes a range of outcome metrics. SalesRep reports 42.5x average ROI, 500K+ conversations per month, 99.9% uptime and 1,000+ businesses across 30+ countries. It also cites a 60% faster sales cycle, an 81% conversion rate with AI Agents and 3x more leads from ads. Customer stories describe AirCharter.com cutting its sales cycle by 60% with the omnichannel inbox for private jet charter bookings, Maroc Ventes eCommerce handling support and sales across WhatsApp, email and live chat from one inbox with 3x faster quotes, Sport Center reaching an 81% conversion rate with AI Agents on SalesRep, and Sip.ma tripling leads and streamlining customer communication. The stated promise is to transform customer conversations into revenue. SalesRep is marketed as built for a range of business types, each with a concrete workflow. Clinics and healthcare use it for bookings, confirmations, reminders and patient follow-ups right inside WhatsApp. Sales teams use it to capture, qualify and close leads from ads and chats in one visual pipeline. E-commerce and retail teams use it for order updates, abandoned-cart recovery and product campaigns that convert. Salons and local services use it for appointment scheduling, deposits and no-show reduction on autopilot. Customer support teams use one shared omnichannel inbox, with AI resolving the routine majority. Real estate and agencies route property and project inquiries to the right agent in seconds. A separate workflow example shows quote requests for hardware being received via WhatsApp, assigned to an agent, tracked through lifecycle stages such as Proposal, Warm Lead and Purchased, and answered with a quote attached. SalesRep targets businesses that sell and support customers through messaging apps — sales teams, support teams, e-commerce and retail operations, clinics, salons and local services, and real estate agencies — and reports being used by 1,000+ businesses worldwide. Integrations named in the content include HubSpot, Salesforce, Jira and Zapier, plus Shopify, WooCommerce and PrestaShop, and the product states it connects to 40+ tools; it also supports Zapier, Make and n8n, API access and webhooks, and Meta & TikTok Ads and Catalog. Pricing starts at $39/mo for the Starter plan with 3 users included and +$12/seat, then $20 per extra 1,000 conversations that never expire, with conversation-per-month tiers of 1000, 2500, 5000 and 10000+. The Growth plan is $79/mo with 5 users, the Advanced plan $139/mo with 10 users, and Enterprise $249/mo with 20 users. A 21-day free trial requires no credit card. SalesRep emphasises safety and onboarding. It uses the official WhatsApp Business API and enforces Meta's messaging policies — opt-ins, approved templates and sending limits — so your number stays safe, and the team helps resolve any issues with Meta. The WhatsApp Business API requires its own dedicated number, which can be new or migrated, and SalesRep guides users through every step. Teams can migrate contacts, templates and automations from other tools or from the WhatsApp Business app without interrupting ongoing conversations. The free trial lasts 21 days with no credit card required, including help connecting channels and launching first automations, with evaluation extensions available on request. Most teams launch within a few days, and guided onboarding is free on every plan. The platform is available in 30 languages and AI agents converse naturally in Arabic (including Darija), French, English, Spanish and more, with a tone you control. AI agents do not replace teams; they take over repetitive work such as answering common questions, qualifying leads and routing conversations, handing anything complex to the right human agent with full conversation context. As a summary, SalesRep combines an omnichannel team inbox, AI sales agents, workflow automation and broadcast marketing into one platform for businesses that sell and support customers across messaging channels. Its central value proposition is that a virtual sales rep can pull live prices and stock, answer in the customer's own language, generate and send quotes, follow up until the deal closes, and hand off to a human whenever needed — turning everyday customer conversations into revenue while reducing response times and manual workload.

kōdlo is an AI-native sales workspace for high-ticket B2B teams. It finds prospects that fit your ICP, tells you how to warm each one up, and writes the message, the offer, and the deck from your own documents. Instead of stopping at a list, the workspace carries a deal through the full cycle: ICP interview, lead sourcing, list enrichment, deep research, cited brief, personalized outreach, pipeline update, campaign content, and closed deal. Your team tracks clients, contacts, and tasks in the same place, so nothing gets lost between steps. An agent sits on every page, and a shared memory layer means the research, outreach, and CRM capabilities never start from zero context. The product positions itself as the AI workspace for sales, built around one source of truth. Most sales tooling solves one slice of the cycle. As the site itself puts it, other sales tools hand you a list and stop. The gap is everything that comes after: understanding whether a prospect genuinely fits, finding the public signals that show how to approach them, writing outreach that sounds like you, and keeping the pipeline current while you do it. When each of those steps lives in a different tool, context fragments — the reasoning behind a lead, the sources behind a claim, and the history of a relationship all get scattered. kōdlo addresses this by holding your ICP, your contacts, your campaigns, and every brief the agent has written in one place, so prospects arrive with their signals and sources attached and stay that way. kōdlo's outbound loop starts with the ICP Builder, an interview-style setup where the agent builds your ideal customer profile with you. From there the Lead Discovery agent hunts for leads that match it, and each lead is backed by real signals rather than a guess. Those signals are drawn from public record sources the site lists explicitly: press releases, patent filings, job postings, trademark registries, conference programs, public funding rounds, open repositories, public LinkedIn pages, podcast transcripts, tender notices, Companies House, and SEC EDGAR. Every signal is cited to its source, so you can check for yourself that the fit is real. A list enrichment step sits between sourcing and research, filling out the records that discovery produces before the agent goes deeper on them. Deep research turns every account into a cited brief. The agent plans the question, runs the searches, cross-checks what it finds, and cites every source — on screen, step by step, while it happens. That visible trace (ask, plan, search, cross-check, cite) is what lets you see exactly where the agent went wrong when it is wrong. Research draws only on public sources, and every record carries the links it came from. The site notes that the record is live and re-indexed hourly, and that the lawful basis for processing is legitimate interest, documented. The result is a brief you can verify rather than a summary you have to trust, which matters a great deal when the account in question is a high-ticket deal where a wrong assumption is expensive. Outreach goes out personalized over LinkedIn or email and is drafted in your tone of voice. What makes it specific is the Knowledge Hub: you upload product catalogues and other documents, the hub parses them with OCR, and the agent turns them into personalized messages, offers, deep searches, and decks. The Knowledge Hub holds up to 1,000 pages on the Starter edition and up to 10,000 pages on Pro. On the closing side, pitch decks and proposals generate from your own template, so a deal that advances or closes turns into campaign content that keeps the account warm. Documents and attachments that arrive through the inbound lane are parsed and made queryable in the same workspace. The workspace pairs tools and agents on one shared context. On the tool side sit the capabilities your team works with every day: outreach, web intelligence, the Knowledge Hub, and CRM operations. On the agent side sit deep research, lead discovery, content and slide-deck generation, and scheduled automation jobs. Everything sits on a single memory layer made up of short-term memory, long-term session-wise memory, and user profiling memory, so no capability and no agent ever starts from zero context. The CRM and contact management keep the pipeline current, holding companies as an entity layer, people in each role, and the industry they move in. A ticket system handles inquiries, replies are grounded in Knowledge Hub citations and the memory of past threads, and Telegram and Google Chat connections deliver follow-ups and digests. Pro adds long-term session memory and agent learning. The stated outcome is continuity: each step feeds the next because they all run on the same data. Open a contact six weeks later, ask "what's next?", and the agent answers from the record it built — grounded in their public profile, their company news, and your own history with them. On the data side, the promise is that you pay for signal rather than seats: no per-contact charges and no data add-ons. Your data stays in your workspace, under GDPR, CCPA, and global privacy standards, with sourcing the site describes as GDPR-clean. Two workflows are described in detail on the site. In the outbound loop, you define the play with an ICP block, the Lead Discovery agent discovers leads, deep research qualifies prospects with cited briefs, and personalized LinkedIn and email outreach goes out in your tone of voice; the flow ends in a close-and-retain stage with pitch decks, proposals, and scheduled check-ins, and wins and losses feed back to refine the ICP. In the inbound lane, incoming inquiries become contacts and tickets with attachments parsed and queryable, every reply is grounded in Knowledge Hub citations and past threads, follow-ups and digests reach you in Telegram and Google Chat, and pitch decks and proposals generate from your own template. Closing and retaining run in the same workspace as the hunt. kōdlo is aimed at high-ticket B2B sales work: solo reps ready to work a real pipeline, small teams sharing one workspace, and organizations whose needs do not fit a standard plan. Pricing runs across three editions. A free tier offers a seven-day trial with one seat, the agent-native workspace, ICP Builder and Prospect Finder, integrated web and deep research, CRM and contact management, Knowledge Hub with OCR, cited deep research briefs, Telegram and Google Chat connection, and the ticket system. Starter is $49 per month plus VAT (about $43 per month on quarterly billing, a 15% saving) for one seat and Knowledge Hub OCR up to 1,000 pages. Pro is $199 per month plus VAT (about $169 per month quarterly) for up to three seats, workspace collaboration features, 4x month limits, long-term session memory, agent learning, and OCR up to 10,000 pages. An Enterprise edition adds custom AI agents built around your workflow, custom integrations, SSO and advanced security, SLA, DPA and procurement support, dedicated onboarding, and an optional bring-your-own-API-key option. Claude Desktop, ChatGPT Work, or your code agent can connect with kōdlo MCP to scale and orchestrate contexts. kōdlo's core proposition is an end-to-end sales workspace with unified context: one record that finds the prospect and answers the inquiry that arrives without one, one memory that every tool and agent shares, and one place where the ICP, the briefs, the outreach, and the pipeline live together. For high-ticket B2B teams, that means the research behind a lead is cited and checkable, the outreach is written from your own documents and in your voice, and nothing gets lost between the steps of the cycle.

AgentSDR is an open-source, self-hosted AI SDR workspace that runs outbound across email, LinkedIn and WhatsApp from a single place, and pairs that outreach with an AI CRM. Teams use it to build sequences, import and enrich lead lists, contact prospects on the channel that fits, and let AI read and classify every reply before an answer is drafted from their own knowledge base. Rather than renting several separate outbound subscriptions, they keep leads, campaigns and conversations in one workspace that they run on their own server with their own model key. The Product Hunt listing positions AgentSDR as the open-source AI SDR workspace that replaces Clay, Smartlead, HubSpot "and many more." The landing page makes the same point visually with a wall of familiar tools — Smartlead, Clay, Instantly, HubSpot, HeyReach, Attio, lemlist, Salesforce, Apollo.io, Pipedrive, Expandi, Close, Outreach, Lusha, Salesloft, Hunter, Waalaxy and folk. Outbound work is normally scattered across sending tools, enrichment tools and a CRM, and each one needs its own subscription, its own data import and its own login. AgentSDR's answer is to put reach, triage and measurement in one workspace: sequences on email, LinkedIn and WhatsApp inside each channel's limits, every reply classified by AI with the answer already drafted, and replies, meetings and customers measured by channel in a single view. Email is the first channel. Sequences run from your own Google Workspace mailboxes, connected through a service account with domain-wide delegation, and they can be multi-step. Any CSV or XLSX column can be used as a {{merge field}}, and {A|B} spin text lets one step read differently per lead. Each mailbox carries its own daily cap (30 by default), sending window and signature, and several campaigns can share the same pool of mailboxes, which are assigned round-robin. List hygiene is handled at send time with one-click unsubscribe and automatic bounce suppression. AgentSDR deliberately does not record opens or clicks, so reply rate is the engagement metric to watch rather than open or click rates. LinkedIn runs through Unipile and can spread sending across several accounts. A typical sequence is an invite, an accept message and three follow-ups. Pacing stays inside LinkedIn's limits: 30 invites a day on premium accounts and 5 on free, with a randomised 30–60 second gap between invites and sending only inside each account's working hours; an account that hits LinkedIn's own limit pauses for the day. Search batches can pull up to 400 leads a day per account into campaigns. Every LinkedIn reply lands in one thread view with an AI draft already prepared, so nothing depends on remembering to check a separate LinkedIn inbox. WhatsApp is the third channel, and it is built around calling. Linking your number through Unipile and installing the AgentSDR Call Recorder Chrome extension lets you dial a lead from AgentSDR; the extension places the call inside WhatsApp Web and records both sides. The recording goes to your own storage bucket and your chosen model transcribes it. Unanswered leads can be called again after 1, 2 and 4 days, and messages sync as well, with a 24-hour warm-up for new numbers and a limit of 25 new chats a day per number. WhatsApp calling relies on WhatsApp Web's English interface. The AI CRM and inbox is where the three channels converge. Every reply is classified as Interested, Customer, Not interested or Other — or into stages you define yourself — and the answer is drafted from your knowledge base and held for approval. Every follow-up step in a reply sequence is drafted for review too. The inbox is keyboard-first: J and K move, Enter opens, and ⌘K jumps anywhere. Autonomy is deliberately narrow. The AI can move a lead forward in the pipeline on its own when it is confident, but a backward move, a low-confidence classification and every new Customer are held for a person. Drafts wait in "Action required" until someone sends them, as written or edited, and analytics track how many drafts went out as-is, edited or discarded, along with the override rate for labels a person changed. Underneath the channels sits one database of people and companies, shared by every channel. You import CSV or XLSX, add your own columns (text, number, date, select) and match duplicates on email or LinkedIn. Enrichment tables go further: a column can call an API, run a formula, ask your model or pull from Apollo, and the finished table can be turned into a campaign directly. Every AI call — classification, reply drafts, transcription and AI table columns — runs on your own OpenRouter key, pinned to the provider you chose, with fallbacks turned off so data only goes where you decided. Leads, conversations and call recordings live in your Postgres and your own storage bucket; recordings are reached only through short-lived signed links, and provider keys are encrypted at rest with AES-256-GCM. There is no hosted AgentSDR service in the middle. Deployment is the other half of the design. AgentSDR is free and open source, and you run it yourself. The quick start is a clone, a copy of the example environment file (database URL, auth secret, encryption key), and docker compose up — after which the app answers on localhost:3000 with Postgres, schema, app and scheduler in place. It needs a machine that runs Docker and PostgreSQL 16 or newer, though the Compose file brings its own database. Because it is a TypeScript Next.js app on Postgres, adding a column type, an enrichment provider or your own channel is ordinary application work, and issues and pull requests are welcome on GitHub. One deployment can also hold several organizations, each with its own leads, inboxes and connected accounts, fully separate from the others; teammates sign in with their own accounts and are invited as owners, admins or members. The benefits follow from that combination. Replies, meetings and customers are measured by channel in one analytics view, so you can see which channel actually brings conversations in, alongside counts of interested, customer, not interested, other and unclassified replies, funnel stages, drafts sent and the override rate. Guardrails run on every channel — daily caps, sending windows, warm-up for new numbers and Do Not Contact honoured everywhere — which keeps sending behaviour inside the limits the channels themselves enforce. Because the AI proposes rather than sends, the human stays in the loop: low-confidence classifications wait for review, and drafts sit in a queue until someone approves them. And because leads, conversations, recordings and model keys stay on your infrastructure, your data is not handed to a third-party SaaS vendor. Concrete workflows follow the channels. A sales team imports a CSV of leads, enriches company data in a table with an AI column, and creates an email campaign from that table, letting the mailbox pool pace itself under daily caps. A founder runs LinkedIn outreach across two accounts with an invite, accept message and three follow-ups, and answers replies from the unified thread view. A rep places WhatsApp calls from AgentSDR, gets a transcript written by their own model, and queues retries for the leads who did not pick up. An agency runs several organizations in one deployment, each with separate leads, inboxes and connected accounts. Throughout, the AI CRM keeps a priority queue of conversations waiting on a person, follow-ups that are due, and drafts to review. AgentSDR targets sales and go-to-market teams, founders doing their own outbound, and agencies running campaigns for multiple clients — anyone who wants multi-channel outreach and an AI-assisted CRM without per-seat or per-contact fees. The integrations it connects are your own accounts: Google Workspace for email mailboxes, Unipile for LinkedIn and WhatsApp accounts, OpenRouter for every AI step, and Cloudflare R2 for call recordings, plus optional lead enrichment integrations for emails, phones and company data in Tables (Hunter, Lusha, RocketReach, Snov, FullEnrich, LeadMagic, Findymail, ZeroBounce, Apollo and others). The stack is Next.js 16, React 19, TypeScript, Postgres, Drizzle, Tailwind 4, Bun and Docker. Pricing is simply free and open source: no seats, tiers or per-contact fees — you pay for your server, the accounts you connect, and your own AI usage. The takeaway is that AgentSDR turns outbound into one owned system: reach on email, LinkedIn and WhatsApp inside each channel's limits, triage where every reply is classified and every answer drafted, and measurement that shows replies, meetings and customers by channel. Because it is open source and self-hosted, your leads, conversations, recordings and model key never leave your infrastructure, and you can change how it works.