Development
Why Enterprise Companies Choose AI Implementation Partners Over DIY ChatGPT Solutions
DIY AI projects look cheap until they touch real workflows, real data, and real users. Here's why most enterprise teams end up working with a partner instead.
DIY costs more than the API bill
Internal AI builds tend to underestimate the work around the model — integrations, evals, security review, ops — and overestimate the work inside the model. A partner that has done this five times before will tell you what's hard up front.
Production is the hard part
A demo that works on three documents is not an AI product. Handling the long tail, monitoring quality, and recovering from bad outputs is where the real engineering lives. Partners bring patterns for all three.
Speed compounds
Three weeks to a useful pilot beats six months to a perfect roadmap. Working systems generate the data and the team confidence that good AI roadmaps need.
How we engage
We start with a tightly-scoped pilot — one workflow, one metric, one team. From there we expand only when the first system is steady and trusted.
Got a similar problem worth solving?
One 30-minute call. We'll walk through the workflow, the data and what we'd actually do. No deck.
