We Build LLM-Powered Features and Tools
Most teams want a GenAI feature — an assistant, a search layer over their own data, something that reads and reasons — but haven't built one before. We have.
The Problem
Everyone's Trying GenAI. Not Many Are Shipping It.
LLMs are easy to demo and hard to ship. A prototype that looks great in a meeting often falls apart with real users — retrieval that pulls the wrong context, answers that change every time you ask, no real way to tell if a change made things better or worse. Getting past that stage takes people who’ve actually built one of these before, and most teams haven’t.
What's Included
RAG system design —
pulling the right context out of your own data before the model ever answers.
LLM application architecture —
how retrieval, prompting, memory, and tool calls fit together as one system.
Prompt and response pipeline engineering —
writing and testing prompts that hold up outside a demo.
Evaluation harnesses —
so you know if a change made the system better, not just different.
How It Works
Scoping —
What you're actually trying to solve, and whether GenAI is the right tool for it at all.
Prototype —
A working version, fast, so you're looking at something real within weeks, not months.
Evaluation & hardening —
Testing it against real cases and fixing what breaks before it's in front of users.
Deployment —
Shipped into your product or workflow — not left as a demo nobody uses.
Why moventAI
Most GenAI projects don’t fail because of the model. They fail because of the engineering around it — retrieval that pulls the wrong context, prompts that were never really tested, no way to measure if a change helped or hurt. We build with that discipline from the start: real retrieval architecture, tested prompts, and an evaluation loop that tells you whether the system is actually working before your users find out the hard way.
Who It's For
- Product teams adding a GenAI feature to something they already ship.
- Internal tools teams building an assistant, a knowledge-search tool, or anything that needs to reason over company data.