Eagentix Autonomous Identity

Data Platform Reviewer AI Agent

Review and optimize your enterprise data platform architectures with our automated Data Platform Reviewer.

Technical Capability Matrix

Designation
Data Platform Reviewer AI Agent
Latency
< 500ms Execution
Security
SOC2 / Air-Gapped
Governance
Policy-as-Code

Autonomous Operation Workflow

  1. Grant read access to metadata, query history and job history.
  2. Set the scope: one platform, or the whole estate.
  3. Let the first pass run and expect it to find more than you wanted.
  4. Triage by cost of leaving it rather than by severity label.
  5. Assign each finding an owner and a fix.
  6. Leave it running so the next accumulation is caught early.

Frequently Asked Questions

What does a review actually cover?

Cost, reliability, security posture and modelling. Where storage is being paid for twice, which jobs fail routinely and are simply retried, what has broader access than it needs, and where the model has drifted from anything anyone would design today.

Is this a one-off audit or continuous?

Either. The first pass is the one that finds the accumulated surprises. Running it continuously catches new ones while they are still small, which is usually the cheaper mode.

Will it just tell us to migrate everything?

No. A recommendation to replatform is easy to make and expensive to receive, so findings come with the cost of fixing and the cost of leaving it. Some things are cheaper to live with, and the review should say which.

Does it need access to our data?

Metadata, query history, job history and configuration. Not the contents of your tables. If a finding genuinely requires looking at data, it says so and asks.

How does it prioritise?

By what it costs you now, not by severity theatre. A misconfigured warehouse burning money every night outranks a naming convention violation, even when the second is easier to write up.

What do we get at the end?

A findings list with evidence, an owner-ready fix for each, and the query or configuration that demonstrates the problem — so an engineer can verify rather than take it on trust.