Discover platforms/Concentric AI

GOVERNATLAS / PRODUCT DOSSIER

Concentric AI

Concentric AI describes contextual data discovery/classification, access governance, remediation, AI guardrails and data-loss-prevention workflows. It presents coverage across data at rest, in motion and used by AI; actual integration boundaries require confirmation.

01 / CONTEXT & SCOPE

Understand the proposition.
Define the boundary.

The decision to make

Test whether context improves the decision your team needs to make rather than accepting a broad classification label. A document can be sensitive because of how facts combine, but a useful finding must still identify an owner, exposure and justified action. Choose a known business context with synthetic examples and counterexamples.

What this record does not establish

No contextual accuracy, comprehensive protection or advertised autonomous outcome is independently measured. Confirm which integrations detect, which enforce and which only forward a signal. Evaluate review/rollback authority, retained document fields and data flows for the selected deployment.

1 current source · 1 published assertion
Source coverage is a research boundary, not a quality score.

02 / YOUR EVALUATION

Turn interest into a useful trial.

Open the evaluation playbook ↗
A

A test worth running

In a proposed pilot, classify a synthetic sensitive document and a similar benign one, inspect the explanation and challenge the false positive. Review an excessive-sharing finding and an intended exception, then follow one approved correction to the source. Test the chosen AI/data-in-motion path separately.

GovernAtlas editorial proposal. We have not performed this test.

B

Evidence to bring back

  1. A classification explanation and dispute record with benign counterexamples.
  2. A source-linked remediation and exception trail plus integration enforcement map.

03 / DOCUMENTED EVIDENCE

Read the claim. Inspect the basis.

Each statement retains its classification and preserved source. A vendor assertion is not an independent test result.

01
vendor asserted

Concentric AI describes contextual data discovery/classification, access governance, remediation, AI guardrails and data-loss-prevention workflows. It presents coverage across data at rest, in motion and used by AI; actual integration boundaries require confirmation.

Source, dates & preserved provenanceConcentric AI — current official product scope ↗

Authority: vendor owned
Observed 2026-10-15 · Reviewed 2026-10-16 · current until 2026-11-14

Artifact SHA-256: 6b99fda5a326d62340e39bfc7797642023ab649b3f55268593577285e6f59a56

The hash identifies the preserved capture. The live source may have changed.

Source register

Concentric AI — current official product scope ↗vendor owned · captured 2026-10-15
Brand asset provenance

Organization identity asset from its official website; inclusion does not imply endorsement.

Official website ↗ · Original asset ↗

04 / BEFORE YOU COMMIT

Better questions.
A clearer decision.

Resolve these with the provider and your own evaluation team.

01

Can you provide a classification explanation and dispute record with benign counterexamples for the selected configuration?

02

A source-linked remediation and exception trail plus integration enforcement map. Who owns and reviews this evidence?

03

Which current version, edition, integrations and operating responsibilities are included?

Regulatory applicability requires a separate, current determination. Inclusion is not certification.

KEEP THE RECORD USEFUL

A dossier should stand up to scrutiny.

Have a source that changes this picture? Submit it for editorial review.

Raise an evidence issue ↗