Risk register and taxonomy
Your categories, your hierarchy, your ownership model. Risks live in the structure your organization already reasons with, not in a generic vendor's default tree.
Risk management software built to measure
Off-the-shelf GRC suites push your process into their model. We build the platform around the framework you already run.
When the GRC suite stops fitting
Most risk functions we meet run on a mix of three things: a licensed GRC tool nobody fully uses, a set of spreadsheets that hold the work people actually rely on, and a shared drive where evidence goes to be forgotten. The tool was bought to standardize the process, and it ended up describing a process nobody follows.
The mismatch is structural. A generic platform ships one risk taxonomy, one scoring model and one approval flow, because it has to serve every industry at once. Your framework was shaped by your regulator, your sector and years of internal decisions. Forcing one into the other produces duplicated controls, evidence that never quite matches the control it belongs to, and an audit that turns into archaeology.
Building the platform around the framework removes that translation layer at the root.
What we build
The risk and compliance platforms we deliver
Scoring and appetite thresholds
Inherent and residual scoring with the formula your committee approved, and thresholds that escalate on their own when a risk crosses appetite.
Controls and evidence
Every control carries its testing schedule, its owner and the evidence attached to the period it covers. No more hunting through drives at audit time.
Immutable audit trail
Who changed what, when and on whose approval, kept in a form an auditor can read without trusting anyone's memory.
Integrations with the systems of record
ERP, ticketing, identity provider and monitoring feed the platform through APIs, so risk data reflects what the business is actually doing.
Reporting for the people who decide
Board packs, regulator-facing extracts and operational views built from the same data, instead of three parallel versions of the truth.
Where this experience comes from
Risk work is where two things we do every day meet: complex enterprise cloud platforms and regulated processes that have to survive an inspection. We have built an ESG platform that collects and redistributes emissions across a supply chain with reporting aligned to ISO and the GHG Protocol, and a compliance hub inside an ERP that tracks mandatory training, instructors and certificates with their retention obligations.
Both are risk systems under a different name: a taxonomy, evidence attached to an obligation, and a trail that has to hold up months later.
You own the code
There is no license fee and no vendor lock-in. Source code, API documentation and repository access belong to the client, on standard and documented technologies. For a system that has to stay auditable for years, being able to change supplier without rebuilding the platform is part of the risk profile.
Frequently asked questions
What risk and compliance teams ask us before starting
All frequently asked questionsDo we have to replace the GRC tool we already have?
Usually not, and not straight away. A common starting point is to build the part the current tool handles worst, connect it to the existing one through APIs, and let the two run side by side. Replacement becomes a decision you make later with evidence in hand, rather than a leap of faith at the beginning.
Which frameworks do you support?
The one you use. Because the model is built rather than configured, the taxonomy and controls can follow ISO 27001, NIS2, the EU AI Act, an internal ORM framework or a sector-specific scheme, including combinations of them mapped to shared controls. They are decided up front and pursued together.
How is evidence kept ready for audit?
Evidence is attached to the control and the period it belongs to at the moment it is produced, with an immutable record of who submitted and who approved it. Preparing for an audit becomes a search and an export, not a reconstruction.
Can AI be used on risk data safely?
Yes, within limits worth stating. Models are useful for classification, drafting and spotting gaps, never as the authority on a decision. Outputs pass schema validation, high-impact and write operations go through human approval, and every step leaves a trace. Enterprise cloud services are chosen so that client data is not used for training.
Can it run on our own infrastructure?
Yes. The deployment target is a decision taken at design time: European cloud, Italian cloud, your own cloud account or on-premise, driven by the regulatory and contractual constraints you work under rather than by our convenience.
Risk is governed on your own framework.
Before you bend to a standard suite, let's talk about how you work today: we tell you whether custom is really worth it.
- You won't talk to a salesperson
- NDA before we get into the details
- The code stays yours