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§ Agent · Feed

The Feed data agent that acts the way you would.

It keeps an eye on every RSS and Atom feed your pipelines depend on, on a schedule you set or whenever fresh data lands. When a source goes silent or the content shape changes, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #data-pipelines
⚠️ product-blog feed silent 62 hours, 4 downstream enrichment jobs stale

The product-blog feed at blog.acme.com/rss.xml hasn't published since Friday 14:12 UTC. Its 7-day baseline is ~1.7 entries/day. Four enrichment jobs that key off new entries are now running on stale data.

Review & approve Dismiss
Feed Entry timestamps + downstream job run logs · reconciled to source site · 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 your feed entries to the tables and jobs they power

It checks the entries arriving from each feed against the warehouse tables and downstream jobs that consume them, then flags the gaps before stale data propagates. You catch a silent feed or a missing entry before it poisons the enrichment pipeline that depends on it.

Feed Entry
Freshness

Know the moment a feed goes silent

It learns the publishing cadence of each feed and watches for the entry that should have arrived and didn't. You find out a source stopped publishing before anyone downstream acts on numbers that quietly went stale.

Feed Entry
Schema drift

Catch a field change before it breaks your parser

When a feed drops a field your pipeline maps, changes its date format, or starts nesting content differently, it tells you which entries changed and what reads from them downstream. You hear about the drift while you can still adjust the transform, not after the load fails.

Feed Entry
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 Feed object, modeled and query-ready the moment you connect.

Feed Entry
engagementgeneral_data_storage

It runs on your real feeds (inconsistent date formats, missing fields, irregular publish cadences and all), 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 Feed, 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 Feed 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.

Your answer engine
is one afternoon away.

Book a 30-minute call and watch us build your first dashboard live, with your own data.