2 Meeting Operations AI Agents, Live in Production.

2 live agents automate meeting operations within operations. They all run on demand. Each one publishes the inputs it needs, the steps it works through and what it hands back.

  • Live

    Calendar Invite Generator

    Turn a plain-language request into a calendar invite with an agenda, ready for your approval. Nothing is sent.

  • Live

    Meeting Notes to Actions

    Turn rough meeting notes into decisions, owned action items, and a follow-up invite — separating what was agreed from what was only discussed.

Separating what was agreed from what was only discussed

Meeting notes conflate three things that need to stay apart: what was decided, what someone will do, and what was merely raised. Written up quickly afterwards, they flatten into a single list, and both failure modes follow. Actions appear without owners, so nobody does them and everyone assumes somebody else is. And discussion items get recorded in the same register as decisions, so an idea floated for consideration reappears three weeks later as a commitment the team is apparently behind on — which is corrosive, because it means the notes cannot be trusted and people stop reading them. The alternative, having someone write the notes properly during the meeting, costs the attention of a participant.

These agents handle the two mechanical parts. Meeting Notes to Actions turns rough notes into decisions, owned action items and a follow-up invite, separating what was agreed from what was only discussed. Making the separation structural rather than a matter of the note-taker’s care is what makes the output reliable. Calendar Invite Generator turns a plain-language request into a calendar invite with an agenda, ready for approval — nothing is sent. The agenda is the useful part: an invite without one is the main reason a meeting has no shape, and writing one is the step that gets skipped when the invite is created in a hurry between other meetings.

What this moves

Actions leaving a meeting with a named owner
Decisions and owned action items are extracted from the notes, so an action without an owner is visible as a gap rather than assumed to be someone's.
Commitments nobody actually agreed to
What was agreed is kept separate from what was only discussed, which prevents an idea raised in passing being recorded as a decision.

Operations

How AI agents handle meeting operations

Drawn from the 2 agents above — what they require, how they run, and what comes back.

What they need

  • What's the meeting?
  • Invite settings
  • Meeting notes
  • Follow-up settings

What comes back

  • Calendar invite Event preview
  • What I had to assume Flagged exceptions
  • Agenda Markdown doc
  • Recap Markdown doc
  • Action items Table of results
  • Decisions made Verification checklist
  • Left unresolved Flagged exceptions
  • Follow-up invite Event preview

How they run

Run on demand
2
Steps per run
3
Credits per run
3–4

Where meeting operations fits in operations

Meeting follow-ups, data quality checks and renewal tracking fall between departments, so they slip. Agents are a good fit precisely because the task is well defined and the owner is not.

All 4 operations agents

Next Step

Deploying meeting operations agents

These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.

Book a Technical Call
  • No sales script
  • NDA on request
  • Scoping notes sent within 48 hours
Call us Book a call