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Technology & Software
AI Prototype to Production
A DEMOBECOMESSOFTWAREYOU TRUST
We take AI prototypes and apps generated with coding assistants and turn them into software a business can depend on, by auditing what exists, closing gaps in security and data handling, and building what is missing.
A prototype proves that an idea can work once, while production means it works every time, for every user, with their data kept safe.
From a convincing demo to dependable software
- 01Prototype audit
- 02Security checks
- 03Production readiness
Prototype to production work starts from something that already runs, whether a model notebook, an agent built in a hurry or an app produced with an AI coding tool. We review the code, the prompts, the data flows and the hosting, list what stands between the demo and real users, and then do the engineering to close that list.
It suits founders and teams whose prototype has earned interest and now has to carry real customers, payments or company data. Much generated code is sound and can stay. Some hides problems that only appear under load or attack. We tell you which parts to keep, which to harden and which to rebuild, with the reasons for each.
Talk to us about your projectCapabilities, End to End
What It Looks Like When It Ships
From Kickoff to Launch
We run and read everything that exists, speak with whoever built it and produce a plain report of strengths, gaps and risks, ranked by what would hurt real users first.
Together we define what production means for this product, including users, data, uptime and budget, and turn the gap list into an ordered plan with a clear point at which launch is safe.
Security and data fixes come first, then tests and evaluation, then the parts that need restructuring. Sound code is kept, and each replaced part is checked against the behavior people already liked.
The product goes live to a limited group with monitoring, usage limits and a route to a person, and access widens as the measurements show it holding up.
Built for Teams Like Yours
What buyers ask before they start
If yours is not here, ask us directly. The first conversation is free and useful whether or not we work together.
Book a callOften a good share of it is. Generated code tends to be readable and to follow common patterns. Its usual weaknesses are missing access checks, secrets left in the code, no tests, weak error handling and database designs that do not scale. We review it as we would review any inherited project and keep what is sound, since rewriting working code for its own sake wastes your budget.
The same short list appears in most projects. Sign-in and permissions, protection of data between users, handling of failures and slow responses, tests, evaluation of model answers, cost controls, backups, monitoring and a repeatable way to release changes. None of it shows in a demo. All of it decides whether the product survives its first real customers.
We can assess it and advise. Some platforms let you export code or connect a custom backend, which gives a path forward. Others keep the logic locked inside. In that case the prototype serves as a detailed specification, and we rebuild the parts that need to scale while you keep using the original to learn from customers in the meantime.
By measuring them. We collect real examples, define what a good answer looks like and score the system on that set whenever a prompt, model or data source changes. Around the model we add validation of outputs, limits on what it may do, fallbacks when it fails and human review for decisions that carry risk. Reliability comes from the system around the model.
Rarely. The plan separates what must be fixed before any real user arrives, such as access control and data protection, from what can improve after launch. Many products go live to a limited group while restructuring continues behind the scenes. We agree that line with you at the start, so the launch date depends on a known list and not on a general sense of readiness.
