AI Operations — Agent Office
AI agent
operations board
The hardest part of adopting AI is not building it. It is knowing whether it is still running. Who is doing what, right now — shown the way an office seating chart shows a team.
Live Demo
Watch the workas it happens.
The board below is running. Select a team to see its detail on the right.
agent_status.json. Falls back to demo mode when not connected
The demo shows six fictional teams. In practice the board is built around your own teams, owners and running jobs.
Does this sound familiar
- Nobody knows if it ran
- The automation is in place, but no one checks whether it succeeded. You find out days after it stopped
- Only one person can answer
- The person who built it knows where the logs are. When they are away, nobody can say what is happening
- No numbers to show
- You want to say the AI is paying off, but there is no figure for how much it actually processed
- Too many places to look
- Every tool has its own console. Nothing shows the whole picture in one view
What it does
- Live status
- Which team, doing what, right now — in a seating-chart layout that reads without technical background
- Hand-off tracking
- Work crossing team boundaries is drawn as a line, so a stall is visible rather than reported
- Schedule view
- Daily and weekly jobs laid out across 24 hours, with planned runs beside actual ones
- Volume history
- Completed counts accumulate per team and per day, giving you the adoption figure directly
- Failure alerts
- A failed job surfaces on the board and is pushed to Slack, Discord or email
- Works with what you have
- Not limited to agents we build. In-house batches, RPA and SaaS workflows sit on the same board
- Built for a wall display
- Designed to stay on an office monitor, so the whole company can see the AI working
From JPY 50,000 (excl. tax). Quoted on the number of targets and integrations; consultation and estimates are free / anything that can emit its state as JSON can be connected / typically 2–3 weeks to deploy, or 1–1.5 months where the state output has to be built / available on its own, or bundled as the operations layer of an AI system we build for you.