Services
AI and Agentic Systems
LLM agents, retrieval, and ML services engineered to do real work in production, not just demos.
Most AI projects die in the gap between an impressive demo and a system you can actually depend on. compute.az builds for the far side of that gap: LLM agents and retrieval systems that run against your real data, under real load, with the guardrails and cost controls that keep them useful past the first week.
We design agentic workflows and tool-using assistants that do work rather than just chat - calling your systems, retrieving from your own documents and databases, and taking bounded actions you can audit. The retrieval layer is grounded in your content, so answers are specific to your business instead of generic.
Underneath the features, the engineering is unglamorous and essential: model selection and evaluation so you know what you are shipping, cost control so a useful system does not become an unaffordable one, and the monitoring to catch drift before your users do. The assistant on this site is a live example - talk to it to see the approach in action.
The same system also has to work at company scale: more than the one team that commissioned it. We roll agentic systems out across the organization using our Forward Deployed Engineering model, embedding with each team that needs it so the same grounded, evaluated system reaches every user who benefits, not just a single desk.
What this covers
- Agentic workflows and tool-using assistants
- Retrieval-augmented systems over your own data
- Model selection, evaluation, and cost control
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