You moved fast with vibecoding using tools like Cursor, Lovable, Bolt, Replit, v0, and GitHub Copilot. Now, Relevant helps founders and product teams turn those AI-generated apps into secure, scalable, maintainable products ready for real users, investor review, and long-term development.
We review the entire AI-generated codebase to identify bugs, performance bottlenecks, and technical debt that could crash your product under real user load.
AI tools often ignore security best practices like authentication, data validation, and secrets management. We close the gaps to protect your user data and IP.
Prototypes are often “spaghetti code.” We refactor the core architecture to make it modular and maintainable, ensuring you can add features without everything breaking.
We add automated testing to the most critical paths of your application, from user sign-ups to payment processing, preventing future regressions.
We build professional deployment pipelines so your team can ship updates safely and frequently without manual errors or downtime.
We document how your application works so future developers can understand the codebase and onboard quickly without constant guidance.
Relevant packages your AI-built prototype into a production-ready system with the final refinements needed for high availability, compliance, and user growth.
You get a full review of your prototype assessed as a production system. Relevant checks the codebase, architecture, security, database logic, integrations, deployment setup, and technical debt, then shows you what is safe to keep, what needs fixing, and what could block launch, investor review, or future development.
Before adding new features, we harden the parts that create the most exposure: authentication, permissions, secrets, API access, payment flows, dependencies, data handling, and fragile logic. The goal is to remove hidden risks without throwing away the product you already built.
You receive a codebase your team can build on. The structure is cleaned up, business logic is separated, APIs are improved, and the database is stabilized, so your team, future hires, or investors reviewing the technology can understand and extend it.
You get the foundation a real product needs to ship and grow: practical test coverage, staging and production environments, CI/CD workflows, deployment documentation, and monitoring basics. Your product can be released, updated, and handed off without every change becoming a new risk.
Once the product is hardened, we help move it into the hands of real users. Whether it is a web app, mobile app, or cross-platform product, we support final deployment, release checks, store submission if needed, monitoring, and post-launch stabilization so your AI-built prototype becomes a working product in the market.
We apply 13+ years of software engineering rigor to AI-generated output, ensuring code maintainability and long-term product health. As a mature software development partner, we are not a new AI trend shop.
We have proven experience building and modernizing custom software across industries. This ensures your AI prototype is delivered with engineering excellence gained from 246 projects delivered.
AI tools prioritize speed over safety. We prioritize security, protecting your users and business from vulnerabilities commonly found in LLM-generated code.
We have experience with GDPR, HIPAA, ISO 27001, cybersecurity, and regulated-industry software development to ensure your product meets necessary regulatory standards.
You work with 92% senior talent who understand how to modernize and scale rapidly evolving AI applications. Our senior engineers review architecture, security, DevOps, and maintainability risks.
Our 96% employee retention ensures stable teams preserve product context from audit through launch and ongoing support.
AI Prototype to Production Services turn a vibecoded or AI-generated prototype into a product real users can rely on. You built fast with tools like Cursor, Lovable, Bolt, Replit, v0, and Copilot and proved the idea works. Now the code needs to hold up under load, pass a security review, and survive investor due diligence. We take that prototype and make it secure, scalable, and maintainable by a human engineering team. The result is a system your team can extend for years, not a demo that breaks the first time real traffic hits it.
AI coding tools optimize for a working demo, not a live system, and that gap is wider than it looks. Three categories of risk usually sit under the surface.
Not necessarily. We secure what works and refactor only what is broken or dangerous, so you keep the speed advantage that got you here.
First we map the risks. Then we harden the parts that create the most exposure and clean up the architecture so your team can build on it. Throwing away working code wastes the runway. Our goal is to stabilize your product as fast as possible while keeping everything that already earns its place in the codebase.
We work with codebases from any major LLM or AI coding tool. That includes Cursor, Lovable, Bolt, Replit, v0, Copilot, and code generated directly from ChatGPT. The build tool you used does not change our process. We assess the code on its own merits: how it is structured, where it cuts corners on security, and what it takes to make it production-grade. Whether your stack is Next.js, Python, or a low-code platform, our team has the cross-platform expertise to stabilize and scale it.
It depends on the state of the code and how far you want to go. A focused security audit and hardening sprint runs as little as two to four weeks, which is enough to close the most dangerous gaps before launch or an investor review. A full architecture refactor with CI/CD setup for a complex application typically takes two to three months.
After we review your codebase, you get a clear scope and a realistic timeline before any work starts, so you know exactly what each phase covers.
Yes, we can. Technical debt from AI tools is a common reason a promising product fails due diligence, so we document the codebase to the standard investors expect. You receive a report covering architecture, security, test coverage, and code quality, with a clear account of what we found and what we fixed. It demonstrates that your product runs on a solid, professional foundation. That matters most during VC funding rounds and M&A cycles, where the technical review can make or break the deal.
You choose how we stay involved. We can hand over the full cleaned-up codebase, cloud setup, and documentation so your internal team takes it from there with no lost context. Or we provide ongoing managed development to help you scale the product and ship new features. Because our teams hold context from audit through launch, backed by 96% employee retention, the engineers who hardened your product are the ones who keep building it. No re-onboarding, no handoff gaps.
We use AI-assisted development to move up to 50% faster and catch up to 20% more bugs than traditional refactoring, while senior engineers make every call on what is safe to keep, fix, or rebuild.
Technical debt from AI tools can fail due diligence. We ensure your architecture, documentation, and security meet the standards required by investors.
Whether your prototype is built on Next.js, Python, or a low-code tool, our team has the cross-platform expertise to stabilize and scale your stack.
We have a 4.9 Clutch rating based on third-party validation from verified clients who highlight transparency, communication, and delivery quality.
Book a call with our experts to discuss your codebase audit, security hardening, or architecture refactor.
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