CEO Sam Liang unveils new tools and vision to turn Otter into the core memory system of the modern workplace
Beyond Notes: Otter’s Big Evolution
Otter.ai, long known for its meeting transcription capabilities, is pivoting into deeper enterprise territory. CEO Sam Liang is spearheading a transformation from a basic AI meeting assistant into what he calls a “corporate meeting knowledge base.”
On Tuesday, the company unveiled a new suite of enterprise tools designed to connect meeting data with company workflows and centralize information that often gets lost in email threads, chats, or team silos.
“We are evolving from a meeting notetaker to a system of record for conversations,” Liang told TechCrunch.
New Features Target Enterprise Integration
The new rollout includes powerful tools aimed at enterprise customers:
- API integrations for platforms like Jira and HubSpot
- An MCP server, allowing Otter to connect with external AI models
- A new AI agent that can search across a company’s recorded meeting notes, transcripts, and presentations
These features are designed to turn passive transcripts into actionable, searchable intelligence, helping companies better track decisions, share context, and avoid silos.
Why Now? The AI Market is Crowded
When Otter was founded in 2016, there were only a few transcription services. Now, the AI meeting assistant market is flooded with names like Fireflies, Granola, and Circleback, riding the wave of the post-2022 AI boom.
Liang believes Otter’s shift to an enterprise-grade knowledge base separates it from those newer competitors.
“We’re building something fundamentally different now,” he said.
Meetings as the New Knowledge Hub
Liang argues that critical company knowledge lives in meetings—from customer calls to product planning sessions. But most of that data goes unused.
- Siloed conversations result in missed updates and misaligned teams.
- Otter’s system is meant to surface and share non-confidential insights across teams while retaining access controls.
“A lot of inefficiency happens because of information silos,” Liang said. “The goal is to make meeting data broadly useful without compromising privacy.”
Privacy Trade-Offs: A Growing Concern
However, Otter’s new ambitions raise ongoing privacy questions.
- Meetings often include small talk or off-topic conversations not meant for broader distribution.
- While users can restrict access to sensitive recordings, Otter does transcribe everything, including pre- and post-meeting chatter.
Compounding these concerns is an August class-action lawsuit alleging Otter recorded conversations without consent and used that data to train its transcription models.
Liang declined to comment on the suit directly, but defended Otter’s mission:
“We’re building this new AI revolution. If you want AI to help, you need to put AI in the meetings,” he said. “More access to information is better than not.”
From Tool to Infrastructure
Otter’s shift is not just about new features — it’s about reframing how companies treat conversation data:
- Instead of treating meetings as ephemeral, Otter wants them to be persistent, searchable knowledge.
- With the right integrations, Otter could function as a knowledge layer across enterprise tools.
This could turn Otter from a productivity app into a core layer of workplace infrastructure — one that listens, learns, and supports organizational memory at scale.
