Sentin-AI · Data discovery & classification

Your privacy policy describes
the data you think you have.

Sentin-AI scans the data you actually have — databases, cloud storage, business applications — and classifies the personal data inside, so you know exactly what lives where. Discovery first; everything else follows.

The discovery loop

Import → scan → classify → act.

STEP 1

Onboard assets

Import data assets from your systems of record — databases, warehouses, cloud accounts — so what we scan reflects reality, not a spreadsheet from last year.

Shipped: automated asset onboarding
STEP 2

Scan where data lives

Lightweight agents connect directly to your systems and inspect real records — finding personal data in places nobody documented and storage nobody remembers creating.

Shipped: 62 catalogued sources — cloud stores, databases, endpoints and business applications. Of the 40 cloud connectors, 28 are proven against provider emulators or the real engine and 12 are not yet; the 19 agent-based sources have no evidence register yet, and we say so rather than counting them as proven
STEP 3

Classify with context

An AI classification engine labels findings — contact, financial, biometric, government identifiers — with sensitivity levels and risk flags per asset.

Shipped: automated classification with role-based access control
STEP 4

Act on findings

Scan results can write into the Consent Tree inventory — the same scan store the platform's own agents feed — and every finding carries remediation status in the Sentin-AI console, so discovery ends in fixes, not another PDF. A critical finding also opens a real compliance task on the Consent Tree side, not only in Sentin-AI's own console.

Built: Consent Tree inventory sync + compliance-task creation on critical findings (enabled per deployment) + in-console remediation tracking
Coverage

62 sources,
three clouds, your endpoints.

Our scanning agents enumerate and scan data stores across AWS, GCP and Azure — from databases to cloud storage to messaging queues — plus the on-prem systems behind your firewall.

one command, full sweepCLI
$ sentinai scan --provider aws,gcp,azure --deep

→ enumerating stores…        127 found across 3 clouds
→ sampling & classifying…    41,206 objects inspected
FINDINGS
  pii.contact      9 stores   (email, phone)
  pii.financial    3 stores   (PAN, account no.)
  pii.identifiers  5 stores   (Aadhaar-pattern ⚠ HIGH)
→ report written · findings synced to inventory
of our 40 cloud data-store types proven end-to-end against provider emulators or the real engine — the other 12 are code we have not yet run against the service, and we say which. The 19 agent-based sources have no evidence register yet
clouds, one consistent finding format
Live actual records inspected — not guesswork from table names
v1.0 generally available since June 2026
A true story we tell on purpose

We ran Sentin-AI on our own database.
It caught us.

Before shipping, we pointed the scanner at our own lead-capture database. It flagged personal data we were holding without a documented purpose — a real finding, in our own backyard, of exactly the kind the DPDP Act penalises. We fixed it, kept the receipt, and kept the habit.

That’s the standard this product is held to: if it can’t find our mistakes, it has no business looking for yours.

Find out what you’re actually holding.

A first scan takes minutes and reads like a revelation. Bring a database; we’ll bring the scanner.

Book a discovery session →