An AI division with a quality bar
AI treated as a product line with evaluation, cost and latency as requirements.
- Client
- JoFunction
- Disciplines
- AI systems, Evaluation, Product design
- Technology
- Evaluation harnesses, Retrieval systems, Model routing
- Evaluation results across a change
- Confidence surfaced in the interface
- Retrieval and context design
- Evaluation results across a change
- Confidence surfaced in the interface
- Retrieval and context design
Overview
JoFunction AI is the division behind our own AI products and the intelligent features inside everything else we build.
The challenge
The gap between a convincing demo and a dependable product is almost entirely measurement. Without it, every change is a guess and every regression is invisible until a user finds it.
Strategy
Make evaluation the first deliverable. A representative set drawn from real inputs, an agreed definition of a correct answer, and a harness that runs on every change.
Design
Interfaces state what the system is confident about and what it is not, and always leave a path to a human for anything consequential.
Engineering
Retrieval and context design come before model choice. Cost per request and end-to-end latency are tracked as product metrics, and regressions block release the same way a failing test does.
Outcome
An AI practice where quality is a measurement rather than an opinion, applied to our own products and to client work.
Technology
- Evaluation harnesses
- Retrieval systems
- Model routing