You built it with AI.We’ll make it production ready.
Engineering Bay audits, repairs and hardens software so you can put it in front of customers with confidence. We don’t care how you built it. We care whether it’s engineered well enough to run in production.
It works. That’s not the same as ready.
AI-assisted development gets you to a working product faster than anything before it, and that speed is worth having.
But a product that runs, with a few customers on it, hasn’t yet answered the harder question: what happens when something goes wrong? A bot scraping your endpoints, a database that needs restoring, an engineer who has to change code no one on the team wrote.
- Exposed secrets
- No automated tests
- Weak authorization
- Fragile data model
- Unbounded queries
- No backups tested
- Duplicated logic
- No observability
- Stale dependencies
- Manual deploys
Inspect → Refit → Harden → Clear → Maintain
Five stages, in order. You can stop after any one of them - most people start with an inspection and decide from there.
Inspect
Establish what you have, and where it stands against production.
Refit
Repair or replace the parts that won’t hold up, and leave the rest alone.
Harden
Security, reliability, operations and the failure cases the prototype never had to handle.
Clear
A systems check against the same criteria, ending in a production readiness rating.
Maintain
Keep it production ready as it changes and the team keeps shipping.
The Bay Inspection
Before you ship it, inspect it. A fixed-scope examination of your repository, architecture, infrastructure, data model, security posture and deployment process.
You get an Inspection Report: what’s solid, what needs attention, what must be repaired before production - each finding with severity, evidence and a recommended fix. No obligation to have us do the work.
Keep the product. Fix the engineering.
Not a rewrite shop
Most systems we see are two-thirds sound. We find the third that isn’t and work on that. A full rewrite is occasionally the answer; it is never the starting assumption.
Not a code-review service
Code is one input. Architecture, data, infrastructure, deployment and recovery matter at least as much once customers depend on the system.
Not anti-AI
Keep building the way you’re building. Our job is the engineering around it: the checks, tests and operational groundwork that speed tends to skip.
You’ve proven it’s useful. Now prove it’s reliable.
The best time to inspect a system is once it has users and before it has many. The idea has proven itself; the engineering hasn’t been examined.
Founders with a working prototype
Customers are using it, and you have a growing sense that the foundation needs checking.
Teams that inherited AI-generated code
No one on staff wrote it, and it needs to become something they can maintain.
Businesses running internal systems
Built quickly to solve one problem, and now the company runs on it.
Investors and acquirers
Independent technical due diligence on an AI-built product before money moves.
Bring your code into the bay.
Tell us what you built and how it’s deployed, and we’ll come back with whether an inspection makes sense and what it would cost.