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§ Agent · Airtable

The Airtable data agent that acts the way you would.

It keeps an eye on your Airtable bases alongside the rest of your ops stack, on a schedule you set or whenever fresh data lands. When a workflow stalls or the data drifts, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #ops-alerts
⚠️ Pipeline tracker has 34 records with no status update in 14+ days, blocking $92K in forecast

These Records in the Deals base haven't moved stages or received a note since early June, well above your ~5-day touch cadence. 11 of them have close dates inside 3 weeks.

Review & approve Dismiss
Airtable Records + Tables · joined to CRM activity and revenue data · audit log

How an agent works

An agent watches one thing and acts on it. Not a workflow, just a standing watch that usually does nothing and acts the moment it should.

◄ repeats on the schedule you set ►

You stay in control

An agent does what you'd do, and only what you've authorized.

The same trusted numbers

It acts on the same governed metrics as your dashboards, and every action is logged and traceable.

You approve anything that writes

It alerts and recommends on its own; anything that changes data is yours to approve.

Try it on a test channel first

Point a new agent at a throwaway channel and watch its judgment before it touches anything real.

No false alarms

It remembers what it already flagged and waits before acting again, so it won't alert you about the same thing twice.

What you can put an agent on

ReconcileACROSS YOUR SOURCES

Tie what Airtable says to what the source systems actually show

It joins your Airtable records to the systems they track (your CRM, your billing, your project tools) and flags where a record says done but the source never moved, or where real progress hasn't made it back to the base. You catch the gap between the tracker and reality before someone makes a decision on stale data.

RecordTable
Stale

Surface the records that have quietly gone cold

When records in a critical table stop moving, miss a status update, or sit in the same stage past their target date, it tells you which ones, who owns them, and how long they've been frozen. You hear about the stall while there's still time to fix it, not when leadership asks why the tracker looks off.

RecordTable
Drift

Catch schema and field drift before it breaks a workflow

When someone adds a field, renames a column, or changes a linked record structure, it flags the change and tells you which downstream automations or integrations are affected. You find out before the Monday report breaks, not after.

TableBase
Custom

Run any Python it needs to get the job done

Beyond alerts and write-backs, an agent can run arbitrary Python, so it can do whatever the task actually requires: call an API, kick off a job, reshape the data, or wire into your own tooling. The action space is yours to define.

Why not just build it yourself?

You could rig one of these with a cron job and a Slack webhook in an afternoon. The watching is the easy part. Here's what you'd own forever, and don't, here:

  • The cross-source join: not one tool's data, but it reconciled against the rest of your stack
  • A trusted, consistent metric: the same number your dashboards use
  • The investigation into why, when something fires
  • A full audit trail of everything it did
  • The upkeep, when the schema drifts or the script breaks at 2am

The data it works from

Every Airtable object, modeled and query-ready the moment you connect.

Record
salesmarketing
Table
engagementgeneral_data_storage
Base
engagementproduct

It runs on your real Airtable workspace (the abandoned bases, the test tables nobody cleaned up, the linked records that point nowhere), not a tidy demo.

Where it acts

Slack

A message in the channel you choose, with the context and a button to act on it.

Email

A summary in the inbox of the people who need to see it.

Webhook

A payload to your own systems, to wire the agent into whatever you already run.

Warehouse write-back

A flag written back to your warehouse for everything downstream to pick up.

Hand off to Fi

Kick the question to Fi to investigate the why and propose the fix.

MCP

Expose it to your own agents and tools over MCP, and drive it from your stack.

Run it in your own VPC or fully self-hosted. Everything it does is pure SQL and Python you can inspect.

Build your agents with Fi

Fi is your AI analyst. It helps you build and customize everything in Definite, including the agents that watch and act.

Fi

Your AI analyst. Ask questions in plain English, and let it help you build and customize everything in Definite, including your agents.

Meet Fi →

Agents

The watchers and actors. Once you've built one, it runs on its own, keeping an eye on what matters and acting the way you would.

Autonomous agents →

Get started

  1. 1Connect Airtable, and the sources it needs to reconcile against. Synced and modeled in an afternoon.
  2. 2See the numbers tie out to what you already trust.
  3. 3Put an agent on one thing you can't afford to miss. Fi helps you build it.
§ FAQ

Common questions

You set the schedule, and it also re-checks whenever fresh Airtable data lands. Each agent watches the one thing you point it at, nothing else.
It alerts and recommends on its own. Anything that writes, whether to a tool, your warehouse, or a customer, is yours to approve. You can also point a new agent at a test channel first and watch its judgment before it touches anything real.
When something fires, it can hand off to Fi to investigate, drilling into the data it has across your connected sources to find what's behind the move, and showing its work.
Those trigger inside Airtable on Airtable data, when the condition fires. This watches continuously, reasons across Airtable plus the CRM and revenue systems your bases are supposed to track, and hands off to Fi to investigate why a workflow stalled, so you catch it before the data is wrong, not after.

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