Security at the end, or never.
Exposed credentials, badly set permissions and data accessible by accident.
AI by product phase · Validation
Going to production is not pushing the code.
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.
What turns up in production.
Unmeasured performance.
It is fast with ten records and falls over with ten thousand.
Accessibility ignored.
A legal and usability barrier, especially on public sector projects.
Four concrete deliveries.
Every point with acceptance criteria in writing. If it does not pass, it does not ship.
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01
End-to-end functional testing
The critical flows, run automatically on every change.
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02
Security audit
Permissions, secrets, dependencies and exposed surface reviewed before opening up.
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03
Performance on real data
Expected load and peak. Optimisation where the number calls for it.
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04
Accessibility and compliance
WCAG, GDPR and the AI Act as applicable. Documented so it can be demonstrated.
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Validation report
What was tested, with what result and what remains as accepted risk.
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Automated suite
Run on every release, not just before launch.
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Launch checklist
Signed before opening to real users.
What we bring from what is already running.
No published case of our own as a validation service, but it is the gate all six pass through before going out. Buscafact handles public procurement data and Match Prácticas handles data on minors on placement: in both, the security audit and access control were not optional. What we transfer is that checklist, not a generic template.
Highest-impact use cases
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01
End-to-end tests on the flows that make money
The critical journeys — signup, purchase, delivery — are automated and run on every deploy. Not everything gets tested: what costs when it breaks does.
The regression shows up before the customer does.
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02
Security audit with prioritised findings
Access, dependencies, data exposure and configuration. Each finding with its severity and its cost to fix, so it can be decided on.
Turns security into decisions rather than fear.
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03
Performance on real data, not laboratory data
Measured with the volume you are going to have, not ten test records. Almost everything holds up in development.
Launch day stops being the first load test.
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04
Accessibility checked, not declared
Contrast, keyboard navigation, screen readers and labelling. Beyond being required, it is traffic and customers lost in silence.
Compliance and reach in the same pass.
What it is built with.
Before you call us, read this.
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9 mistakes when hiring custom software development (and how to avoid them)
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.
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How to scale an MVP without rewriting it from scratch
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.
- Discovery Which problem deserves software and which does not.
- Design Architecture, flows and data model before the code.
- Build Code with tests, reviewed and signed off by an engineer.
- The AI inside Agents and models integrated where they multiply.
- Operation and scale Live, measured and with the internal team in charge.
Not sure where to start? Measure your organisation’s AI maturity for free in 3 minutes, or book 30 minutes of direct diagnostic.
Let's start
Let's talk about your operation.
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