Doclium
PDF and document tools plus AI Q&A with citations: merge, split, compress, convert, OCR, and structured extraction workflows.
AI, Document intelligence, SaaS
AI Built the Prototype. I Help Make It Production Ready.
AI tools can accelerate a prototype. Before real users and payments arrive, I review the boundaries that a working demo does not prove: identity, data access, environments, failures, and deployment.
Get a production readiness reviewKeep useful code and expose hidden assumptions
Review the product regardless of whether it started in Replit, Cursor, or another tool. Trace sign-in and role permissions, look for hard-coded credentials, and identify duplicated rules. A successful happy path does not demonstrate that another user’s data is protected.
Verify the money and data paths
Payment retries, webhooks, migrations, and environment configuration need explicit behavior. Create a staging path and test failure recovery before changing production data. Fix the risky boundaries before spending the budget on broad cosmetic refactoring.
Make the system operable
Document deployment, configuration, rollback, and the diagnostic events needed to investigate failures. My own AI and web products provide product-building context; they are not presented as client rescue case studies.
Related product work
TopLLM
Helps users compare LLMs and choose the right model for coding, reasoning, learning, images, and cost, with plain-English recommendations over benchmarks.
AI product, LLM evaluation, Web
Before we start
Does AI-generated code always need a rewrite?
No. Keep code that is understandable and behaves correctly. Replace or repair parts where the risk and maintenance cost justify it.
What access is useful for the review?
Start with a product walkthrough, known blockers, and a description of the stack. Repository access and a safe test environment can follow through an agreed secure process.