Security at the end, or never.
Exposed credentials, badly set permissions and data accessible by accident.
AI by product phase · Validation
Before launch we check that it works, that it holds up, that it is accessible and that it does not expose what it should not. The final approval is signed by a person, always.
Exposed credentials, badly set permissions and data accessible by accident.
It is fast with ten records and falls over with ten thousand.
A legal and usability barrier, especially on public sector projects.
Every point with acceptance criteria in writing. If it does not pass, it does not ship.
The critical flows, run automatically on every change.
Permissions, secrets, dependencies and exposed surface reviewed before opening up.
Expected load and peak. Optimisation where the number calls for it.
WCAG, GDPR and the AI Act as applicable. Documented so it can be demonstrated.
What was tested, with what result and what remains as accepted risk.
Run on every release, not just before launch.
Signed before opening to real users.
Custom builds go wrong for almost always the same reasons: choosing on price, not insisting on owning the code, going in with vague requirements. These are the 9 most expensive mistakes and the concrete questions to avoid each one before signing.
A lot of MVPs die precisely when they start working: the users arrive, the data arrives and the architecture put together in a hurry starts to creak. The good news is that scaling almost never means starting from zero. This is the no-hype guide to doing it in phases.
Not sure where to start? Measure your organisation’s AI maturity for free in 3 minutes, or book 30 minutes of direct diagnostic.
Tell us what costs more than it should. We come back with a concrete plan, realistic timelines and a clear yes or no.
contacto@plantekia.com