The AI partner for teams shipping real models.

Computer vision, NLP, sports analytics, LLM/RAG, generative and agentic AI — across both annotation work and end-to-end engineering. We take on projects where careful data and rigorous evaluation move the needle.

Both. Annotation is where most engagements start. From there we can take it to training, evaluation, fine-tuning, deployment, and ongoing maintenance — depending on what you need.

Yes. Homography, multi-object tracking, ball tracking, event detection, dot-map generation — composable as a full pipeline or per stage. See the Sports Analytics page.

Access-controlled environments, audit logs on annotation tooling, NDAs and DPAs available, region-restricted compute on request. We've worked with PII, healthcare, and financial data under contract.

Yes — supervised fine-tuning, LoRA/QLoRA adaptation, instruction tuning, and evaluation. Our pipeline starts with a clear definition of what 'better' means for your task, before any training run.

End-to-end: ingestion, chunking strategy, embedding choice, retrieval evaluation, answer grounding, and feedback loops. We treat retrieval quality as a first-class evaluation problem.

We start from the outcome: which loop, by whom, with what tools, against what metric. From there: tool/skill design, orchestration, guardrails, and an evaluation harness. No agent demos that stop working in week two.

Shared after a first discovery call, scoped to your project. Annotation work is volume-based; engineering engagements are sprint or retainer. We send a written scope and pricing doc after the first conversation.