~/vairlabs/ai $ model.fit(data)
Division 01

AI / ML research, built to ship.

We design, evaluate, and deploy machine-learning systems — from agentic LLM applications to retrieval pipelines and the MLOps that keeps them honest in production.

Start a project → See Security division
Focus areas

From frontier idea to running system

We don't stop at a demo. We measure, harden, and deploy — then keep iterating against real-world signal.

  • Agentic systems & tool-using LLM applications
  • Retrieval-augmented generation & knowledge pipelines
  • Fine-tuning, evaluation harnesses & red-teaming
  • Model deployment, observability & cost control (MLOps)
  • Computer vision & structured-data modelling
eval.py — vair-ai
# benchmark a candidate pipeline
from vair import Pipeline, Eval

pipe = Pipeline("rag-v3")
report = Eval(pipe).run(
  suite="production",
  redteam=True)

# → accuracy 0.94
# → p95 latency 380ms
# → safety PASS ✓
Engagements

Ways we work with you

◈

Build

Greenfield AI features and products, designed and delivered end-to-end.

🔬

Evaluate

Independent benchmarking and red-teaming of your existing models and agents.

⚙

Operate

MLOps, monitoring, and continuous improvement once you're live.

Stack: Python PyTorch Claude / LLM APIs Vector DBs Docker Eval harnesses

Have a model or agent to build?

From prototype to production — let's scope it.

Talk to the AI team →