TransAI Note: The Private AI Notetaker Built for In-Person Meetings

An in-person meeting is more than a stream of spoken words. It includes the diagram on the whiteboard, the slide that changes the discussion, the name of the person responsible for the next step, and the reasoning behind a decision.

Most meeting records preserve only part of that picture. A transcript captures what people said. A photo saves the final whiteboard. Personal notes record what one person had time to write down. But the connections between the conversation, the visual context, and the decisions can still disappear after everyone leaves the room.

TransAI Note began with an ambitious product mission: to capture entire in-person meetings and transform them into decisions, action items, and lasting knowledge on a dedicated device.

That mission shaped the hardware, software, and AI models as one system for in-person meetings.

Why In-Person Meetings Are Hard to Capture

People may sit at opposite ends of a large table. A presenter may speak while walking across the room. Several participants may talk in quick succession. Important context may appear on a whiteboard, diagram, slide, or projected screen rather than in the spoken discussion.

The result can be a fragmented meeting record:

• Audio without the diagram that everyone was discussing
• A whiteboard photo without the reasoning behind it
• Action items without clear owners
• A summary that misses team-specific names, acronyms, or technical terms
• An unresolved question that gets separated from the next meeting

An AI notetaker built for in-person meetings needs to capture more of the room and preserve how its different parts fit together.

Far-Field Audio Captures More of the Conversation

TransAI Note uses an 8-microphone array, custom far-field processing, and sound-source localization to capture speech from as far as 15–20 meters.

This matters in conference rooms, training sessions, workshops, and other shared spaces where participants are not speaking directly into one microphone. The dedicated device is designed to capture speech across the room as the discussion moves among participants.

A 50MP Wide-Angle Camera Preserves Visual Context

Some of the most important parts of a meeting are never spoken aloud in full.

A team may point to a section of a whiteboard and say, “Let’s use this approach.” An engineer may revise a diagram while explaining a constraint. A presenter may move between slides as the group compares options. Without the visual content, the transcript can be accurate but incomplete.

TransAI Note uses a 50MP wide-angle camera to bring whiteboards, diagrams, slides, and projected content into the same meeting record as the conversation.

This reduces the need for someone to pause the discussion, take out a phone, and photograph the board. It also keeps the visual reference alongside the discussion it helped shape. Teams can return to both after the meeting and review the context behind a decision.

On-Device AI Turns Meeting Context Into Useful Outputs

Capturing a meeting is only the first step. The record becomes useful when people can find what matters and act on it.

On-device models turn the captured context into transcripts, translations, and structured summaries that include:

• Decisions
• Owners and action items
• Risks
• Open questions

This structure helps a team move from a long recording to a practical account of what happened and what should happen next. A project lead can review assigned work. A participant who missed the meeting can see the decisions and supporting context. The next meeting can begin with unresolved questions instead of reconstructing the previous discussion.

Organizational Knowledge Helps Recognize Your Team’s Terms

Every organization has language that general speech-recognition systems may not understand immediately: employee names, product names, internal acronyms, client terminology, and specialized technical vocabulary.

TransAI Note uses organizational knowledge to help recognize the names, acronyms, and technical terms a team uses. This helps preserve the specific language behind decisions, assignments, and follow-up work.

Multi-Meeting Memory Carries Unfinished Work Forward

Important work rarely fits inside one meeting.

A risk identified on Monday may need an update on Friday. An open question may depend on information from another team. An action item may remain unresolved when the next discussion begins.

Multi-Meeting Memory carries unfinished work into the meetings that follow. This helps teams preserve continuity across a series of conversations rather than treating every recording as an isolated file.

Over time, meeting notes can become a connected record of how decisions developed and what still needs attention.

Core AI Note-Taking Functions Work With Wi-Fi Off

For sensitive meetings, where the processing happens matters.

TransAI Note is built around on-device AI. Its core functions continue to work with Wi-Fi off, and meeting content does not need to pass through TransAI servers for these core functions.

This gives teams greater control over sensitive meeting data while producing transcripts, translations, and structured summaries on a dedicated device. It also allows the core meeting functions to remain available when a reliable internet connection is not.

What a Private AI Notetaker Should Capture

A useful meeting record should connect the conversation with the whiteboard, diagrams, slides, decisions, owners, risks, and next steps that give those words meaning.

That is what TransAI Note is designed to do:

• Capture voices across an in-person meeting room
• Preserve whiteboards and projected content alongside the conversation
• Turn meeting context into structured summaries and action items
• Help recognize the language specific to an organization
• Carry unresolved work into future meetings
• Keep core AI note-taking functions on the device, even with Wi-Fi off

The meeting ends. The board may be erased and the room may empty. The decisions, context, and next steps should remain clear.

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