Problem

Read AI addresses meeting overload and the fragmentation of knowledge work across meetings, email, and messaging. When calendars are packed, employees have less time for substantive work, while note-taking, follow-up, and finding past decisions create a hidden coordination cost. Read’s central use case is to make a meeting reliably useful even when someone cannot attend: capture the conversation, identify its topics and action items, and give participants a concise record they can search and share. Read reports that its users attend 20% fewer meetings and that enterprise search saves 20 hours per month, although these are company-reported outcomes rather than independently verified results.

Product / Service

Read is a cross-platform AI copilot delivered as a software service, with free individual access and paid Pro and Enterprise plans. Its meeting assistant can join meetings, record and transcribe them, and generate recaps, notes, topics, action items, Q&A, highlights, and playback. It works across Zoom, Google Meet, Microsoft Teams, and in-person meetings, with desktop and mobile access, so users do not need a separate assistant for each conferencing platform.

The product is expanding from meeting capture into connected workflow intelligence. Read can answer questions across meetings, emails, and messages, summarize Gmail, Outlook, Slack, and Teams activity, and send meeting reports into collaboration, CRM, and automation tools such as Slack, HubSpot, Salesforce, Zapier, and webhooks. The benefit is less time spent documenting and reconstructing conversations, greater continuity for people who missed a meeting, and a searchable layer of context across the tools where work happens.

Market

Read competes in the AI meeting assistant and meeting-intelligence segment of the broader productivity AI and conversation-intelligence markets. Its differentiation is breadth: rather than focusing only on transcription or sales calls, it positions one assistant across meetings, email, messaging, enterprise search, and workflow integrations. Its competitive set includes Otter.ai, Fireflies.ai, Fathom, Fellow, and Gong, with Gong more specifically focused on revenue intelligence and the others overlapping in meeting notes, transcription, and conversation analysis.

Read is a commercial, funded company rather than a pre-revenue project: it offers paid Pro and Enterprise subscriptions alongside a free tier. The latest quantified traction in the supplied evidence is from 2024. TechCrunch reported more than 100,000 new accounts after the Series A and said that sign-ups, active users, and monthly recurring revenue doubled in less than six months; Read’s October 2024 announcement said the Series B brought total funding to $81 million and claimed 100,000 new accounts weekly, 81% first-month retention, and adoption by 75% of the Fortune 500. The evidence does not provide a verified current revenue figure, so funding, account growth, retention, and enterprise adoption are the clearest disclosed traction indicators.