AI & Machine Learning

LLM applications, custom ML models, and intelligent systems built for production — not demos.

AI built for production

We design and ship LLM applications, RAG systems, and custom ML models for production workloads. Every system we build is observable, evaluable, and operates inside real business constraints — privacy, latency, cost, accuracy.

What we build

Retrieval-augmented chat assistants, document Q&A systems, classification pipelines, recommendation engines, computer-vision systems, agentic workflows, and custom model fine-tunes when off-the-shelf APIs don't fit.

Privacy-first

Many of our clients can't send data to a public API — healthcare, finance, defense-adjacent, internal enterprise data. We build for private deployments: on-prem inference, VPC-isolated services, VPC peering to your existing cloud, no data egress to third parties.

Evaluable by default

Every AI system we ship comes with an evaluation harness — golden datasets, automated regression checks on prompt/model changes, and observability so you can see exactly what the system is doing in production. No black boxes.

Frequently asked questions

Do you build with OpenAI / Anthropic / open-source models?

All three. We default to OpenAI/Anthropic for speed-to-market when privacy allows, and to open-source (Llama, Mistral, Qwen) for private deployments or high-volume cost optimization. We help you choose based on your data sensitivity, latency budget, and cost ceiling.

Can the system run on our own infrastructure?

Yes — we routinely deploy models on private GPU infrastructure (AWS, GCP, on-prem). For sensitive workloads we keep everything inside your VPC with no egress to public APIs.