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Custom ML models and intelligent automation that give you competitive advantages. From predictive analytics to AI-powered user experiences — built, measured, and maintained in production.
End-to-end ML model development: data preprocessing, feature engineering, training, validation, and production deployment.
Copilots, chat interfaces, and structured generation wired into your product surfaces with eval harnesses from day one.
Vector search, hybrid retrieval, cross-encoder reranking, and citation pipelines tuned to your data.
Automated quality scoring, golden datasets, and drift alerting so every release is measured, not vibes-checked.
PII redaction, prompt-injection defence, content safety, and bias detection baked into every model boundary.
Model registries, A/B testing infrastructure, shadow deploys, and low-latency serving with cost tracing.
Chunking, embeddings, reranking, and citations — engineered and measured, not guessed. We tune retrieval against your real data until answers are grounded and traceable.
Every model behaviour is measured. We ship an eval harness with your product so you can prove quality, catch regressions, and sleep at night.
Define the use case, success metrics, and eval criteria. Audit existing data. Lock scope and model selection.
A working AI slice on your data — measured from day one against the eval harness we defined in discovery.
Guardrails, observability, and infra. Shadow-deploy against production traffic, then ship to real users.
Monitor evals, tune retrieval, retrain on new data, and expand capability as usage grows.