I will audit and rescue your stalled ai or llm codebase and get it to production

Most AI projects do not fail on the model. They fail on data, scope and a codebase nobody wants to own.

I founded Shispare in 2012 and we have shipped 100+ projects. I audit AI and LLM builds that have stalled and tell you plainly what is worth keeping.

What you get:

- A read of the actual repo: architecture, data pipeline, prompt and retrieval design, evaluation, cost per call, security.

- A risk register ranked by what will break first in production.

- A salvage or rebuild verdict with the reasoning, not a sales pitch.

- A costed roadmap to a working version.

I came up as a product manager, not an engineer, so the first question I ask is where the money leaks in your workflow, not which model you picked. Often the honest answer is that AI is not the right tool for the job, and I will say so before you spend more.

Typical clients: a proof of concept that will not survive real users, an agency handover you cannot read, a RAG pipeline that returns confident nonsense, or an AI feature that costs more per call than it earns.

Message me with the repo size, the stack and what is going wrong. If I am not the right person I will tell you that too.