kōdlo

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.