Developer Portals
A single front door: service catalog, docs, ownership and scorecards.
Developer platforms, golden paths and self-service tooling — so engineers move fast with guardrails, and leaders get consistency and control.
We treat your internal tooling as a product: a self-service platform where the secure, compliant path is the easy path. Teams ship features, not plumbing.
Paved roads, not bottlenecks.
As engineering orgs grow, inconsistency taxes velocity — each team wires its own pipelines, infra and standards. A platform makes the right way the easy way, and lifts cognitive load off product teams.
A single front door: service catalog, docs, ownership and scorecards.
Paved-road templates with security, observability and CI/CD wired in.
Reliable, policy-gated pipelines and progressive delivery.
On-demand environments within guardrails, via clean IaC.
Security and compliance encoded as policy — enforced by default.
DORA and golden-signal insight that proves impact.
Experienced engineers own the work and AI accelerates it — never the other way around. This five-phase model is how we apply the Braindoos AI Engineering Framework: AI participates in every phase, calibrated to the work; a human owns every decision; approval is always human and standards always override AI.
AI accelerates requirement analysis, research and impact assessment; engineers define, validate and approve the requirements and own the architecture. No unvalidated assumption reaches the build.
AI generates code and tests at speed against approved standards; engineers own the code, the reuse and security decisions, and the architecture. AI does the heavy lifting; the engineer owns the result.
AI pre-screens every change — AI-assisted or hand-written — against the same standards and checklists; experienced developers make the final review judgment. "The AI wrote it" is never a defense.
AI generates tests for both expected and failure paths alongside the code; engineers own coverage and test adequacy and add the manual testing that judgment requires.
AI assists release notes, monitoring and production analysis; engineers approve every release, accept residual risk and decide on every fix. Continuous human oversight, AI-accelerated.
A look at the problems we've solved and the results that followed.
A European enterprise software company’s platform gives each customer a private, per-account knowledge base built from documents they upload, which the platform’s AI can then answer questions against.
Read Case Study →WordPress does not, by default, give a theme a single place where a page’s template, styling and behavior are declared once and consumed everywhere they matter — left to the platform’s defaults, that structure tends to scatter into per-page conditionals or a page builder’s own configuration.
Read Case Study →A European enterprise software company runs a required CI validation sequence against its frontend application, including an automated dependency-security check as one of the required steps.
Read Case Study →Book a consultation with our senior engineers. We'll discuss your current state and map a practical path forward — no obligation, no generic pitch.
Tell us the problem you're trying to solve. You'll speak with experienced engineers who can assess it honestly and outline realistic options — whether or not we end up working together.