AI & ML
AI & ML Solutions
We build production AI systems: chat assistants grounded in your own data, agents that complete multi-step tasks, and pipelines that extract structure from messy documents. Every system ships with evaluation, guardrails, and a cost model, not just a prompt.
Where this fits
- Support or ops teams are drowning in repetitive, language-heavy work
- You want an AI feature but no one on the team has shipped one in production
- A prototype worked in a demo but fails on real, messy input
What’s included
- Use-case scoping and feasibility spike
- RAG pipeline or agent architecture design
- Model selection and prompt/eval framework
- Vector database and retrieval integration
- Guardrails, monitoring, and cost controls
- Human-in-the-loop review workflows where needed
How it runs
- 01
Feasibility spike
A short, paid proof-of-concept against your real data before committing to a build.
- 02
Architecture
Design the retrieval, orchestration, and evaluation layers.
- 03
Build
Iterative development with a living eval set so quality is measured, not guessed.
- 04
Operate
Monitoring, cost dashboards, and a feedback loop for continuous tuning.
Common questions
Ready to talk about ai & ml?
Tell us what you're building. We'll follow up within one business day.