Two Service Lines
| Service | Scope |
|---|
| Security Assessment | Web and API application testing, external infrastructure, source code review, cloud configuration, and the attack surface of systems that use language models. |
| Custom AI Engineering | Design, build, and operation of AI systems for day-to-day operations: customer service, sales, voice and chat agents, document automation, through to private model deployment on your own infrastructure. |
Working Principles
- ✓ Evidence before claims. Every finding comes with reproduction steps that can be re-run from a clean state. Findings that cannot be reproduced do not go into the report.
- ✓ Honest about limits. We state what was not tested and what could not be completed within a single engagement — not only what was successfully found.
- ✓ Actionable language. Every finding has a business impact, a measurable severity, and remediation steps the engineering team can act on immediately.
- ✓ Client confidentiality. Client names and engagement details are not published without written consent.
- ✓ Your data stays with you. When required, work and models run on your own infrastructure, including air-gapped configurations with no outbound access.
Standards Coverage
Every engagement is mapped to industry-recognized frameworks, so the results can be compared, audited, and used as internal compliance evidence.
Who We Serve
- Companies that treat product security as a business requirement (fintech, SaaS, healthtech, e-commerce).
- Critical infrastructure and public service providers that cannot afford a single incident.
- Product teams that want to run AI in real workflows, with data that must not leave their jurisdiction.
Next Steps
The process starts with a single email. We reply with scoping questions, then send a proposal with a clear scope, timeline, and cost.
Start Scoping