Compliance Assessment
Each AI system is assessed against the regulation text, not a checklist.
- Cited to the article
- Multi-jurisdiction
- Evidence collected as you go
You leave withA gap analysis a regulator can follow
NiyamR governs the AI you run, secures every prompt it receives, and attacks your applications, APIs and AI stack before anyone else does. Every finding comes with proof.
$ scan --mode quick staging.example.com
reconmapping attack surface
exploittesting access control on /api/orders/{id}
validatereproduced with a second account
Proof-of-concept attached. Reproduction steps included.
reportwrite-up and SARIF ready
Blocking AI just pushes it out of sight. Make safe use the easy path.
Point us at one target. A Quick Scan runs the same agents as a full test, with a shorter budget. No long scoping call, no procurement cycle.
A Quick Scan is a first look, not a full penetration test. It covers what it analysed in the time it had. Authorized targets only.
The parts feed each other. A finding from a test becomes a task with an owner, AI Security blocks the gap on live traffic, and every action is kept as evidence.
Can you prove your AI complies?
Find the AI in your organisation, assess it against the regulation text, and keep the policy and the evidence in one place.
Each AI system is assessed against the regulation text, not a checklist.
You leave withA gap analysis a regulator can follow
Finds the AI tools and integrations nobody registered.
You leave withA complete AI asset registry
One policy set, mapped to every jurisdiction you operate in.
You leave withOne rule set, enforced everywhere
A record of what was assessed, decided and enforced, ready for a reviewer.
You leave withReports ready for audit
Ask in plain English. Answers come from your own data and the regulation text.
You leave withAnswers your team can act on
What leaves your company in a prompt?
Controls that sit in the path of AI traffic. Detection runs on your own hardware, so prompt text never reaches a third-party model.
Checks every prompt, paste and file attachment before it leaves the user’s machine.
You leave withEmployees keep using AI, without the leak
An inline proxy for the AI API traffic your applications send. Prompts and replies are both checked.
You leave withOne enforcement point for every AI call
Shows what your agents and MCP servers can be made to do, and keeps it contained.
You leave withA risk map of every agent and tool
Would you find it before an attacker does?
Not only AI. A team of agents tests your web apps, APIs, code and cloud, exploits what it finds inside a sandbox, and reports only what it can prove. Pick the depth: quick, standard or deep.
Fast checks on one target. The same agents as a deep test, on a shorter budget.
You leave withValidated findings, the same day
The balanced option for routine testing. Broader than a quick scan, faster than a deep test.
You leave withA routine assessment you can repeat every release
Full-depth recon, exploitation and validation. Agents share discoveries and chain vulnerabilities.
You leave withA full pentest report with a PoC per finding
The same tests on every pull request, scoped to the changed files.
You leave withNo release ships untested
How does your AI hold up under attack?
Conventional scanners do not cover model servers, LLM gateways or agents. This does, and it validates a finding before it reports it.
Finds the exposed and vulnerable parts of your AI stack.
You leave withConfirmed exposures, not version guesses
Measures how your model holds up under sustained attack.
You leave withA success score per attack method
The full assessment as one scoped engagement, with one evidence pack.
You leave withEverything a buyer or auditor asks to see
| Manual pentest | Static scanner | NiyamR | |
|---|---|---|---|
| Time to result | Weeks | Minutes | Minutes to hours |
| Findings | Validated | Unvalidated, noisy | Validated, with PoC |
| How often | Once or twice a year | Every build | Every change |
| AI stack coverage | Depends on the tester | Rarely | Models, MCP, agents |
| Fix verification | A new engagement | Re-scan | Re-test included |
Stop the leak, then test the surface.
Red teaming runs only against systems you own or have written permission to test. A clean result covers what was in scope, not what was left out.
The extension runs in watch-only mode. See what it would have caught.
Your AI register built, scored against the rules, and ready for audit.
One system attacked, fixed and re-tested, with a shareable report.
Gateway, network feed and one policy enforced across the company.
A security tool that leaked your prompts would defeat its purpose. Ours is built so it cannot.
Backed by Innovate UK · NVIDIA Inception
Start with the registry. Every rule runs in monitor mode on your own hardware until you have seen your own traffic and decided what to turn up.