Your code, your data.
Handled with care.
Letting an outside team into your codebase or your client's site is a matter of trust. Here is plainly how we handle access, data and confidentiality, and the security practices we build into everything we ship.
Six practices we follow on every engagement
Least-privilege access
We ask for the narrowest access that gets the job done: a preview URL rather than production, read-only where possible, scoped tokens rather than shared passwords. Access is revoked when the engagement ends.
Your data stays yours
Client code, documents and customer data are never used to train AI models. When we use third-party AI APIs, we use providers and settings that do not retain or train on submitted data, and we tell you which ones upfront.
Careful handling of credentials
Secrets are shared through a password manager or your own secret store, never over chat or email, and are deleted from our side at handoff.
Private delivery
Reports, recordings and code are shared through private links or directly in your repository. We delete review materials once the engagement is complete, or sooner if you ask.
Secure-by-default engineering
Software we build ships with input validation, security headers (CSP, HSTS, frame protection), rate limiting on public endpoints, and dependency checks as standard, not as an upsell.
Guardrails for AI features
AI features we build validate model output against schemas, screen inputs for prompt injection, redact personal data where it is not needed, and are tested against an evaluation set before release.
Want an NDA first?
Happy to sign a mutual NDA before you share anything sensitive. Send us yours, or ask for ours. Your code, your clients and your numbers stay confidential either way.