Meeting and knowledge agent
Turn meetings into actions and answers.Turn meetingsinto actionsand answers.
The agent summarizes, captures decisions and answers questions from approved sources. Knowledge stays usable instead of disappearing into notes.
- Notesbecome tasks
- Sourcesapproved
- Knowledgefindable
Use case
When knowledge disappears after meetings.
Value is high when decisions, tasks and context regularly get lost or reporting consumes too much time.
- Notes disappear
- Meeting outcomes live in personal documents or chat threads.
- Tasks stay unclear
- Nobody knows exactly who should do what by when.
- Knowledge is scattered
- Documents, notes and decisions are hard to find later.
Solution
Structured knowledge instead of note chaos.
The agent summarizes, separates decisions from tasks, points to sources and escalates when information is missing or uncertain.
- Capabilities
- Create summariesExtract tasksMark decisionsSearch sourcesPrepare reporting
- Boundaries
- no hidden sourcesno hallucination as factno tasks without contextno uncontrolled sharinghuman review for sensitive content
Process
From meeting material to usable knowledge.
The pilot starts with approved sources and clear output formats for your team.
- 01
Sources
Which meetings, documents and knowledge sources may be used?
- 02
Output
Which formats does your team need: tasks, decisions, summary, FAQ?
- 03
Agent
Build summary, search, source references and review process.
- 04
Quality
Continuously check correctness, source grounding and adoption.
Trust
Answers that stay verifiable.
Internal knowledge work needs source grounding, permissions and a clear statement when something is uncertain.
- Source grounding
- Answers are tied to approved sources and documents.
- Permissions
- Not everyone should see every piece of information.
- Review
- Critical summaries or decisions can require approval.
Reading
Related articles from the blog.
Practical guides that explain the same processes before you start a pilot.
Meeting agent: notes you can find again
Meeting agent with a team example: separate decision log from tasks, measure baseline, check transcript faithfulness, and run a narrow pilot.
AI scheduling agent: fewer no-shows, clearer calendars
AI scheduling agent with a worked example: separate no-shows from late cancels, measure baseline, reminders with cancel links, and when an agent is needed.
Automation or AI agent before the pilot
Automation, AI assistance or agent: which level fits when. Decision matrix for risk, cost and operations before your first AI pilot project.
BitAutor Meeting Agent
Should meeting knowledge stay usable?
Then we clarify sources, output formats and review boundaries.
Book a 30-minute slot directly whenever it fits your schedule.