Shadow is a real-time AI sales assistant designed for sales representatives, managers, and revenue leaders who want to improve conversation outcomes. The product runs natively on Mac and listens during live calls on any platform, serving contextual prompts, answers, and reminders without interrupting the flow. Its core value is enabling reps to sell better while the call is still happening, turning every conversation into a productive step toward closing deals. Shadow is built by Converse AI Inc., founded by Shubham, Mayank, and Hersh, with a mission to give every seller a personal AI that knows their accounts and their team's collective experience.
The pain point Shadow addresses is the significant time and quality loss in sales calls. Reps often walk into calls cold, with context buried in old recordings or scattered across tools. They lose the thread mid-conversation, forget key objections or pricing details, and then spend an average of 42 minutes after every call on homework like writing follow-ups and tracking action items. Managers waste ten hours weekly reviewing call recordings to spot risks and coaching opportunities. Tribal knowledge stays locked in reps' heads, and win/loss analysis becomes folklore from the loudest rep. Shadow eliminates these pain points by providing real-time assistance and automating post-call tasks.
The first major feature group is Contextual Live Assist. During a call, Shadow listens and analyzes the conversation against team history, account data, and prior calls. When a hard question lands—like pricing objections or competitor comparisons—Shadow surfaces the exact answer the rep needs, citing the source call. For example, if a client asks about pricing scaling per seat, Shadow reminds the rep they quoted platform pricing and should hold the line. This works because it draws from actual won deals and plays from the team, giving reps confidence and eliminating cold moments. The assistant also tracks agenda coverage and meeting prep in real time, flagging hurdles like pricing not yet covered.
The second major feature group is post-call automation and action item tracking. After every call, Shadow automatically captures meeting notes, drafts follow-up emails, and identifies action items from the conversation—assigning them to specific owners. These action items are tracked to completion, with direct links to calendar scheduling or email drafting. The product captures all follow-ups so nothing slips through the cracks. Managers and reps receive a Monday digest summarizing key risks, coaching opportunities, and pipeline hygiene, with receipts from actual call clips. This turns a weekly ten-hour review into a 30-second read, letting managers focus on high-impact actions.
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The third feature group is the Team Memory and Intelligence Desk. Every call feeds a growing cited knowledge base that captures plays, facts, objections, and account updates automatically as the team talks. No forms, no wiki—the system builds itself from real conversations. New hires can ask questions like "How do we handle pricing on 50+ seat deals?" and get answers from the team's memory, citing the exact call clip where that pitch was used. The Intelligence Desk allows anyone to query across all conversations, such as top loss reasons or which feature requests repeat. This delivers institutional knowledge that stays when people leave, reducing ramp time from six weeks to weeks.
Shadow works by running natively on the rep's Mac, joining any call platform (Zoom, Google Meet, Teams, etc.) without needing a bot. It integrates with Gmail, Outlook, Google Calendar, Notion, Slack, Salesforce, Jira, and Linear to pull context and push actions into existing workflows. During calls, Shadow listens and provides live assist. After calls, it auto-generates follow-ups and tracks tasks. The team memory is built continuously as reps talk, with every entry cited to the call it came from. The platform supports 60+ languages for transcription and assist, making it globally applicable. The workflow is seamless: the rep focuses on the conversation while Shadow handles context retrieval, note-taking, and action assignment.
Concrete use cases include a new sales rep ramping quickly by asking Shadow team-specific questions, bypassing weeks of shadowing. A manager receives a Monday digest showing that a champion went quiet on a $48K deal, with the exact quote from the call and a suggested action. During a live call, a rep facing a security review objection gets an immediate answer from a past closed deal, increasing credibility. Post-call, action items are automatically captured and tracked to completion, saving 42 minutes per call. The intelligence desk allows CXOs to analyze win/loss reasons from 847 conversations, identifying top loss causes like insufficient Salesforce depth. Outcomes include shorter ramp, fewer lost deals, and less manual work.
Shadow targets sales representatives (SDRs and AEs), sales managers, revenue operations teams, sales enablement professionals, and CXOs. It works on macOS currently, with Windows in development. Pricing starts with a free tier offering the first 5 hours of calls, then $20 per seat per month for Pro (locked for 12 months), with Team and Enterprise plans for larger organizations. The product is early-stage, with founders actively involved and a direct Slack channel for Pro users. Shadow differentiates itself from conversation intelligence tools like Gong by helping reps during the call rather than reporting after. It is a personal AI that works in front of the rep, backed by the entire team's memory, ensuring smarter conversations and faster deal closure.