Bureau Agent

Agentic operations · for volunteer-run associations

Your association's busywork, investigated by an agent.
Every decision stays yours.

Boards run events on top of their studies: registrations, fees, teams, rooms, trips and dozens of messages. Bureau Agent finds what needs attention, investigates it with tools, and proposes one action with its evidence. Nothing is sent, changed or booked until an organizer approves it.

Explore on my own

The guided demo shows the highlights; the full tour covers every feature. Both use the live agent on fictional sample data.

31issues detected automatically in the sample hackathon
90%correct action type on 50 labeled messages (gpt-4.1)
0actions taken without an organizer's approval
  1. 1
    Detect

    Fixed checks read registrations, payments, teams and the inbox, and list what needs attention, blocking first.

  2. 2
    Investigate

    An AI agent chooses tools, looks up records and rules, and proposes one action with evidence. Rules that must hold are enforced in code.

  3. 3
    You decide

    Approve, edit or dismiss. The approval is what changes data or sends a reply, and it is logged.

The problem

Student boards run real operations with no operations team.

Scattered records

Registrations in a form, fees in a bank export, teams in a spreadsheet, questions in the inbox. Nobody sees the whole event.

Mistakes found too late

An unpaid fee, a member in two teams or a missing room shows up on the day, when fixing it costs the most.

Every answer needs a lookup

"Can my friend from another school join?" means reading the rules and the records before replying, dozens of times a week.

Operations console

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Filter issues

Filters change this list only. Event totals and toolbar actions cover the whole event.

Why you can trust it

The AI investigates. Code enforces the rules. People decide.

Nothing happens without approval

The agent only proposes. Every data change, reply and payment link waits for an organizer, and each approval is logged.

Rules checked in code

Eligibility, team sizes and budgets are verified by code, not by the model. Below a 0.70 identity match the agent must ask instead of acting.

Transparent by default

Each proposal shows the tools used and the evidence found. Drafted replies say they were written with AI assistance (EU AI Act, Art. 50).