AI & software assurance
Three self-hosted testing engines for regulated organisations: synthetic users that pressure-test your AI assistant in Azerbaijani, agents that run your business workflows as regression tests, and penetration testing that starts after the login.
Request a pilot on your dataThe problem
Non-deterministic
Assistant answers vary by phrasing, history and language — fixed test cases don’t cover it.
Scripts break
A UI change breaks test selectors even when the business process still works.
Once a year
Manual pentests are annual while the application ships every sprint.
SaaS is a non-starter
Cloud testing tools need screenshots and working logins to internal systems.
What you get
Realistic synthetic users — varying by role, goal, tone and language, including adversarial and code-switching conversations — run against your chatbot and are scored by an Azerbaijani-native judge.
Describe a business workflow in plain language; computer-use agents execute it through your real interface, across multiple roles, screenshot by screenshot.
A scripted sign-in hands the scanner real sessions, so it reaches the roles, forms and APIs behind the login — where the findings that matter are.
How it works
Deployment & trust
All three engines are self-hosted and share one encrypted credential store. Screenshots of internal data, working logins and scan traffic stay on your infrastructure.
Who it’s for
Test at scale and triage failures instead of hand-writing cases.
Authenticated scanning on every release, inside the perimeter.
Evidence that an assistant or application was tested before launch.
Gate releases and compare versions on a clear score.
In oil, gas & energy
Prove an HSE or engineering assistant answers correctly before it reaches the field.
Regression-test procurement, permit or maintenance workflows across roles on every release.
Pentest the authenticated surface exposed to contractors and vendors.
FAQ
No — it adds a layer. Deterministic scripts keep the stable flows; agents take the long, multi-role, frequently changing ones.
Scans only run against targets explicitly added to an allow-list, and we agree scope and windows with you in writing.
Related
Cited answers from your documents and SOPs, on an Azerbaijani-native language model inside your network.
Fine-tuned models, agentic workflows and complete AI products, built for your process and deployed privately.
Not sure where to start? A fixed-scope discovery sprint maps your use cases first.
A pilot runs on your documents, calls or records — measured against criteria we agree up front.
