Service
LLM features built around one task
An LLM demo is easy to make and hard to trust. We pick one task, write the evaluation set first, and then build. Every change to a prompt, a model or a retrieval step gets a score, so “better” means something.
In three steps
How an LLM feature is built
Define
One task in one sentence, with what is in scope and what the feature must refuse.
Measure
Real examples with expected answers or a rubric, scored by a runner you can start with one command.
Build
The simplest version first, then retrieval, tools or agent steps only where the score says they help.
01 Who it is for
Teams that want an LLM to do one clear job: sort incoming requests, pull fields out of documents, answer questions from their own material, or draft a reply for a person to check. It fits best when a demo exists and nobody can say how good it is.
02 Signs you need it
- The demo works on the examples its builder chose.
- Prompt changes are judged by reading a few answers and feeling better.
- Nobody can say whether a newer model would help or hurt.
- The cost and the waiting time per request are unknown.
- Users find the failures, and nobody collects them.
03 What you get
- A task definition
- One sentence, the inputs, the outputs, and what is out of scope.
- An evaluation set
- Real examples with expected answers or a rubric, agreed with your expert.
- A runner
- Scores any version of the feature against the set with one command.
- The feature
- Built up from the simplest version that works, measured at every step.
- Cost and speed
- What each request costs and how long it takes, measured, not guessed.
- A failure log
- Live failures collected, so the set grows from real use.
All of it is code in your repository, running in your accounts.
04 What we need from you
- Real examples of the task, with personal data removed if needed.
- Time from a person who knows what a good answer looks like.
- Access to the model provider you use, or your rules for where data may go.
- Your rules for what the feature must never say or do.
05 What a first pilot looks like
The task definition, the evaluation set and the runner come first. Then a simple baseline is scored, and one or two improvements are measured against it. You leave with a number you can track, and the code that produces it.
The scope, the price and the length are agreed in writing before it starts. How a pilot works.
06 When we would say no
- A search box, a form or a few rules would do the job. We will say so.
- Nobody can describe a good answer, so nothing can be measured.
- Every answer must be right, and no person will check the output.
Next
An LLM demo you cannot measure?
Tell us the task, who uses it, and what a wrong answer costs. An engineer replies.