Turn your AI-built prototype
into software you can trust.
WR Dev Labs audits, hardens, deploys, and documents AI-built MVPs for founders, agencies, and healthcare-adjacent teams preparing for pilots, investors, customers, or internal rollout.
- ArchitectureNeeds review
- Auth & permissionsHigh risk
- Data handlingNeeds review
- DeploymentNeeds review
- ObservabilityHigh risk
- TestingHigh risk
- DocumentationHigh risk
Your demo may work. The risk is what you can’t see yet.
Before a prototype touches real users, real data, or real business decisions, six things tend to break — and they break quietly until they don’t.
Demo-grade auth and unclear role boundaries break the moment real users sign up.
Where data lives, who can see it, and what gets logged is often unclear in AI-built code.
“Works on my machine” isn’t a deployment plan. Staging, secrets, and rollbacks need real wiring.
Without structured logs and error reporting, you can’t see what’s actually happening in production.
AI-generated code can hide structural issues that only show up under change or scale.
If your next engineer can’t pick up the system without you, the work isn’t done.
Built fast? Now make it real.
You shipped a working prototype with Lovable, Bolt, Replit, Cursor, v0, or Claude Code. Now investors, customers, or pilots need more.
The demo lands. Then the client asks about auth, hosting, AI reliability, and handoff. Bring in a senior technical partner.
Sensitive workflows, patient-adjacent experiences, research operations. HIPAA-aware, GCP-aware, audit-trail-minded engineering.
Evaluating whether a prototype is real enough to fund, pilot, or scale. Get a senior technical read before the check clears.
Start with a senior technical read of what you already built.
A fixed-scope review of the prototype, repo, architecture, deployment approach, data flows, risks, and next-step options. No commitment beyond the audit.
- Production-readiness scorecard
- Risk register
- Architecture observations
- Refactor / rebuild / extend recommendation
- Deployment & environment notes
- Security & sensitive-data considerations
- Prioritized next-step roadmap
Real deliverables. Not slide decks.
- ArchitectureNeeds review
- Auth & permissionsHigh risk
- Data handlingNeeds review
- DeploymentNeeds review
- ObservabilityHigh risk
- TestingHigh risk
- DocumentationHigh risk
- Auth coupled to demo provider with no role modelHighIntroduce role-based access and session boundaries before pilot.
- API keys committed to client bundleHighMove secrets server-side; rotate keys; add env-scoped config.
- No environment separation between dev and prodMediumStand up staging env + deploy pipeline with environment-scoped secrets.
- AI calls lack timeouts, retries, or fallbackMediumWrap calls with guardrails, structured logging, and graceful degradation.
- No logging or error reporting in production pathMediumAdd structured logs and an error reporter before user traffic.
- Production-readiness scorecard
Category-by-category status across architecture, auth, data, deployment, observability, testing, and docs.
- Architecture diagram
A clear picture of what you have today and a target architecture for what production looks like.
- Risk register
Specific risks, impact ratings, and concrete recommendations — not generic best-practice copy.
- Productionization roadmap
Sequenced next steps with effort and dependencies so you can scope sprint work or hand it to your team.
- Handoff documentation
Architecture notes, runbooks, and environment docs written so the next engineer can actually own the system.
Pick the entry point that fits where you are.
Starting ranges, not fixed quotes. Final scope is set after a short call so we’re quoting against the actual work.
Ranges are starting points and reflect typical scope. Final pricing depends on codebase complexity, integrations, and production-readiness goals discussed during scoping.
Production-minded engineering for sensitive workflows.
HIPAA-aware, GCP-aware, audit-trail-minded. We help teams evaluate and harden software that touches sensitive workflows, patient-adjacent experiences, research operations, or healthcare data pathways.
Technical engineering review and implementation support — not legal, regulatory, medical, or compliance-certification advice.
- Role-based access
- Audit trails
- Data minimization
- Environment separation
- AI boundaries & disclaimers
- Documentation for review/handoff
A senior engineering practice — not a generic agency.
WR Dev Labs is a small, senior practice built for the stage where prototypes have to grow up. Experience spans regulated industries, team leadership, and production delivery — applied to AI-built MVPs that need to become real software.
Fast prototypes are useful. But production software requires judgment, boundaries, observability, maintainability, and handoff.
- Senior engineering, hands-on
- Regulated-industry experience (clinical research, healthcare-adjacent)
- Team leadership executing production systems
- AI integration with evaluation & guardrails
- Architecture, deployment, and handoff documentation
Before you launch, fund, or hand off the prototype, know what you actually have.
Get a senior technical read on the work in front of you — and a clear next step.