Ship models. Keep systems healthy

Move AI from experiment to production with repeatable releases and measurable quality. Track models, data, and prompts, watch performance in the real world, and turn operational signals into actionable alerts.

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Custom design

Production engineering

Senior & staff-level expertise

Launch + operations

No AI slop. No template churn.

AI can accelerate research, implementation, and iteration. It does not get to make product, design, architecture, testing, security, or launch decisions unattended.

We build the thing people will actually use: opinionated design, conventional engineering discipline, explicit quality gates, and enough operational thinking to keep the launch from becoming someone else's cleanup project.

Outcomes worth shipping

01Reproducible model releases with clear approval and rollback paths
02Visibility into model quality, data drift, latency, and inference costs
03Quicker incident triage with actionable operational signals
04AI systems that remain observable, secure, and maintainable over time

Strategy through production

MLOps pipelines for training, validation, deployment, and model registries
LLMOps prompt and dataset versioning, regression evaluations, tracing, and guardrails
AIOps anomaly detection, alert correlation, and human-reviewed incident triage
CI/CD for ML models with automated evaluation gates and canary rollouts
Data and feature pipelines, experiment tracking, and reproducible workflows
Production inference monitoring for quality, drift, latency, cost, and reliability
Access controls, observability, rollback, and cloud AI deployment operations

Bring us a real constraint

ML teams turning notebooks and experiments into production services

Product teams operating LLM features and AI agents at scale

Operations teams seeking smarter detection and investigation of system issues

Build the right surface, not the fashionable one

AI infrastructure Data engineering DevOps & CI/CD AI product development

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