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§ Agent · Amazon S3

The S3 data agent that acts the way you would.

It keeps an eye on the files landing in your S3 buckets and the tables they feed, on a schedule you set or whenever fresh data lands. When a load breaks or a schema drifts, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #data-pipelines
⚠️ events/ dump landed 41% light, downstream session model at risk

Today's events partition wrote 612K rows against a ~1.04M daily baseline, and 3 new columns appeared that your schema doesn't map. Looks like a truncated upstream export.

Review & approve Dismiss
S3 File Object + Schema · reconciled to warehouse row counts · 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 the files in S3 to the tables they feed

It checks the rows and partitions landing in your buckets against the warehouse tables they load and the source systems that produced them, then flags the gaps before your models run. You catch a truncated export or a missed partition while it's still a file in S3, not after it's poisoned every dashboard downstream.

File ObjectDatasetRecord
Schema drift

Catch a schema change before it breaks the load

When a new column appears, a type shifts, or a field your pipeline depends on goes missing, it tells you which objects changed and what reads from them downstream. You hear about the drift while you can still adjust the mapping, instead of debugging a failed dbt run at 7am.

SchemaFile Object
Freshness

Know the moment an expected drop doesn't land

It learns the cadence of each prefix and watches for the file that should have arrived and didn't, or arrived far smaller than usual. You find out a feed is stale before the stale numbers reach anyone who'd act on them.

File ObjectDataset
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: re-trigger a load, parse a malformed file, reshape a partition, or wire into your own orchestration. 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 Amazon S3 object, modeled and query-ready the moment you connect.

Dataset
general_data_storagecustomerengagement
File Object
general_data_storagecustomerengagement
Record
general_data_storagecustomerengagement
Schema
general_data_storagecustomerengagement

It runs on your real buckets (mixed file formats, half-documented prefixes, columns nobody mapped yet), 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 Amazon S3, 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 Amazon S3 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.
You could rig an S3 event trigger to a Slack webhook in an afternoon. What you'd own forever, and don't here: the join back to the warehouse and the source system, the trusted row-count baseline, Fi investigating why the load came up short, and the audit trail behind every flag.

Your answer engine
is one afternoon away.

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