AI readiness · Data governance
AI is here. And it’s here to stay.
Let’s do it responsibly — for your safety, and for your success.
Your third‑party map, checked against what was actually shared.
Every scan records the external domains your data reaches — so the register stops being a list someone maintains by hand.
Decisions from data. Evidence from the record.
Every classification, every posture change, every data point kept — so what you claim is what you can show.

Your business. Your data. Our agent. Your safety.

2019

Working in data governance since 2019 — classification, retention, access.

2020

Running our own SaaS platform since 2020 — we operate what we sell.

Now

AI readiness, built on that foundation. And this is just the beginning.

Why readiness starts with governance

AI is only as safe as the data you feed it.

Know your data

A catalogue of what you hold, where it lives, and how sensitive it is — before any model touches it.

Govern the access

Identity risk, privileged accounts and external sharing under watch — so AI never widens exposure.

Prove it

Snapshots, comparisons and evidence — a defensible record of how your posture moves.

Governance, end to end

From a scan of your estate to evidence you can hand over.

Five steps, in the order the work actually happens. Each one is a page in the portal, not a services engagement.

  1. 01 CONNECT

    Register the sources

    Microsoft 365 and cloud tenants, Entra, and every datasource you want read — each with its scanner group and sensitivity tier.

  2. 02 SCAN

    Look for what matters

    A template says what a scan looks for — the classifier rules it matches values against. Bound to its sources, it becomes a profile you can run, stop and watch.

  3. 03 EXTRACT

    File the facts

    Findings, paths, permissions and file metadata land in your own metadata catalogue, each object stamped with the scan it came from.

  4. 04 CLASSIFY

    Apply your policy

    Your classification levels and their match rules run against the catalogue — as a dry run first, with a full history and a rollback.

  5. 05 PROVE

    Take the data point

    Snapshots of identity risk, sharing, retention and GDPR posture, compared over time. See the reporting

Facts first, judgement second.

Extraction records what was found and assigns no sensitivity of its own. The level is derived afterwards, from your policy — which is what lets you reclassify the whole estate without scanning it again.

The gaps show themselves.

Objects of one shape classified several ways, classified data in public teams, sensitive objects with no owner — the catalogue surfaces the rule you have not written yet, and an automation can alert on it the next time posture moves the wrong way.