Practice 06
AI Engineering
Retrieval systems, agents, document understanding and evaluation harnesses — built as production software rather than demos. We start from the task and the data, not from the model.
On the axis
Intelligence end
The question it answers
How will you know when the model is wrong?
Capabilities
- LLM integration into existing products and workflows
- Retrieval-augmented generation over private corpora
- Agentic workflows and tool-using systems
- Document understanding, extraction and classification
- Computer vision for inspection and monitoring
- Evaluation harnesses and regression suites for model output
- MLOps: versioning, deployment, drift and cost monitoring
- Data pipeline engineering upstream of any model
What you receive
Concrete artefacts, handed over and yours to keep — whether or not the engagement continues.
- 01
A working system against your data, not a sandbox demo
- 02
Evaluation set and measured baseline you can re-run
- 03
Guardrails, fallback behaviour and human-in-the-loop points
- 04
Token and inference cost model at expected volume
Tell us what is not working.
A short conversation is usually enough to tell whether we are the right team for the problem. If we are not, we will say so and point you somewhere better.
- info@chozar.com
- Phone
- +91 97144 65486
- Office
- Ahmedabad, Gujarat
- Hours
- Mon–Sat, 10:00–19:00 IST