This Is GRC

An AI-native GRC system, in working pieces

Build GRC that knows what is happening.

Bring signals, enterprise context and practitioner judgment together. Then give a person a decision they can actually make.

Vendor, control and risk signals join enterprise intelligence and practitioner heuristics before reaching a human decision.

Choose your problem

Start with the work on your desk.

Pick a problem. See the signals, add context, then open the working Lens.

TPRM Lens · fictional replay

I have too many vendors to monitor.

Public notices, vendor documents and internal use can change before the next review.

Open the working TPRM Lens
01 / Collect

Follow the signal trail

Vendor document, procurement and identity signals lead to different actions for Sales and CRM Platform.

Illustrated from the fictional replay

02 / Interpret

What does this mean here?

Reading with context

Sales sends live customer calls. CRM Platform tests in a synthetic lab. Same vendor, different decisions.

Enterprise intelligenceTeam, data flow, approval history, and how the use began.

Practitioner heuristicA changed data flow reopens the vendor decision.

Explore the demoCompare the two Nimbus AI engagements, then run the Vendor Surface replay.

Build your first versionJoin one public or vendor update to procurement, sign-ins, and two real team uses.

Build a first version of TPRM Lens from your own work
  1. Write the decision first: which change in a vendor or its use should reopen review?
  2. Collect one vendor or public update, one internal adoption signal, and the actual data flow for each team. Keep source and date beside every fact.
  3. Interview yourself about what would make you continue, pause, or escalate. Replay the rule against two uses of the same vendor.

What you should have: One engagement record that links the signal, team, data flow, decision rule, and named owner.

The layer underneath every Lens

Know the enterprise, not just the feed.

Which team uses the system? What data moves through it? What work is already open? Enterprise intelligence connects those facts to the signal. That is why one vendor can call for two different answers.

Nimbus AI has one vendor signal, but Sales uses live customer calls while CRM Platform uses a synthetic lab. The GRC action differs.

The hardest part to build

Teach the system how you decide.

I used ChatGPT Voice Mode to interview me about decisions I had made. “Low risk” was not enough. It asked what made it low risk and which fact would change my answer. That questioning turns tacit judgment into rules you can test.

Explore the Heuristics Lens

Put it together

Build one useful loop before a platform.

Start with one recurring decision. Connect its signals and business context. Extract a practitioner's rule. Replay it on a past case before you trust it.

About the sample data and source

The guided cases use fictional companies, teams and internal records. TPRM Lens also has a separate portfolio of real public vendor evidence, clearly marked in the product. The Lenses replay fixed examples without an account or API key. The TPRM source and sample data are public on GitHub: you can change a fictional engagement there and rerun it locally. The combined site source is currently private while it is prepared for public release.