Knowledge from your meetings, or from everything your team writes.
Otter.ai is a strong meeting notetaker that now doubles as a knowledge engine: it records and transcribes your calls and makes what was said searchable, with agents that act on meetings. this+that builds a company brain too, but from a different and much larger source: the messages your team sends all day across email, Slack, Teams, Google Chat, and Telegram. Meetings still count: the transcripts and summaries that land in your inbox get read like any other message. One captures, all day, what gets said in meetings; the other captures, all day, the operational knowledge spread across everything your team writes.
A meeting knowledge engine, or a company brain fed by every message
Otter.ai made a smart move in 2026: it grew from an AI notetaker into what it calls a Conversational Knowledge Engine, turning meeting transcripts into searchable institutional knowledge with agents that schedule, capture action items, and qualify leads. Its AI Chat Connectors now pull live context from tools like Gmail, Notion, Jira, and Salesforce, and Otter can feed its meeting history to ChatGPT and Claude as an MCP server. If meetings are where your company's knowledge gets created, Otter captures that layer well, at real enterprise scale.
The difference is what each captures continuously. Otter's always-on capture is meeting audio: it records calls from Zoom, Meet, and Teams and turns what was said into searchable knowledge. Its AI Chat Connectors now reach further, making Otter an MCP client that pulls live data from Gmail, Google Drive, Notion, Jira, and Salesforce (with Outlook, Teams, SharePoint, and Slack on the way) into Otter AI Chat, and it acts as an MCP server too, so tools like ChatGPT and Claude can tap your meeting history. That is real cross-app reach. But the thing Otter captures automatically, all day, is still the spoken meeting. this+that's always-on capture is the written message stream itself: every email, Slack message, Teams message, and more, read as it arrives. Most operational knowledge lives there, in the thread, the decision, the customer's reply, the quiet handoff, and this+that builds its brain from that whole stream, folding meetings in too: the transcripts and summaries that land in your inbox get read like any other message. The idea is similar; the source is different, and much wider. On top of that you get a unified inbox and workflows, which Otter does not have.
Feature by feature
How the two products compare across the things that matter most.
| Topic | Otter.ai | this+that |
|---|---|---|
| Category | Conversational Knowledge Engine built on meeting transcripts, with meeting agents (action items, SDR, recruiting). | Universal inbox plus a company brain built from every message, with workflows that act on what arrives. |
| Knowledge source | Primarily meeting and voice capture (Zoom, Google Meet, and Teams calls, desktop and mobile recording, audio and video uploads), plus context pulled from connected apps. | Every channel your team writes in (email, Slack, Teams, Google Chat, Telegram), plus the meeting transcripts and summaries that land in your inbox. |
| What it ingests | Meeting audio captured continuously, with live data pulled on demand through AI Chat Connectors via MCP (Gmail, Google Drive, Notion, Jira, Salesforce, with more on the way). | The actual content of your messages across every connected channel, read continuously for tasks, context, and knowledge. |
| Where knowledge comes from | Mostly what was said out loud in a meeting, plus context pulled on demand from connected apps. | The operational knowledge spread across everything your team writes, the missing middle, plus what is said in meetings. |
| Where work starts | A meeting happens and gets recorded. | Any message arrives, on any channel, and the agent reads and acts on it. |
| Agents and automation | Meeting agents: action item capture, scheduling, and SDR and recruiting agents that work off calls. | Workflows triggered by your messages: 32 action types, conditional logic, loops, and MCP, that both read the brain and write back to it. |
| Unified inbox | Not an inbox. A meeting layer alongside your tools. | A rebuilt unified inbox across every channel, where the work and the knowledge live together. |
| The knowledge loop | Meetings feed the knowledge base; agents act on meetings. | Messages feed the brain and the workflows; workflows act on messages and write back to the brain. It compounds. |
| Buyer | Meeting-heavy teams and enterprises; priced per user with an enterprise tier. | Teams whose work lives in messages across many channels. |
| Pricing | Free tier, Business around $19.99 per user per month billed annually (higher month to month), enterprise custom. | Free during beta. |
- Otter is one of the best meeting notetakers there is, and the move into meeting knowledge is well executed. If your institutional knowledge is created in meetings, it captures that layer thoroughly.
- Voice-activated agents that join the meeting and answer questions or capture tasks in real time are a genuinely useful idea.
- Channels group recordings by team, project, or topic, so meeting history is searchable in one shared place.
- AI Chat Connectors pull live context from Gmail, Notion, Jira, Salesforce, and more into Otter AI Chat, and Otter works as an MCP server so tools like ChatGPT and Claude can draw on your meeting history.
- Real enterprise scale and a mature product, with the security and admin features large orgs expect.
- If meetings are the job, Otter and this+that work well together: the summaries Otter emails you get read by this+that like any other message, so meeting knowledge joins the rest of your brain.
- The knowledge that never gets spoken: the email thread, the Slack decision, the customer reply, the quiet handoff. this+that captures the written operational stream meetings miss.
- A universal inbox across email, Slack, Teams, Google Chat, and Telegram, with every message read for tasks and context.
- Workflows that act on incoming messages and write back to the brain, so knowledge grows as a side effect of doing the work.
- Meetings still count: the transcripts and summaries that land in your inbox get read like any other message.
- A company brain that grounds every workflow and answer in what your team actually decided, across channels, not just calls.
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