MLOps that keeps production AI reliable, and affordable.
Deployment pipelines, monitoring, cost ceilings, and fallbacks for teams running real models in production.
Shipping a model is the easy part. Keeping it accurate, fast, and inside budget for months is the hard part, and it's where most AI projects quietly fall over.
The layer that keeps AI alive in production.
CI/CD for models and prompts
Every change runs through evals before it reaches production.
Monitoring and drift detection
Catch quality drops and data drift before your users do.
Cost ceilings
Token budgets, per-tenant dashboards, and model fallbacks that keep spend predictable.
Incident response
Alerting, on-call, and clean rollback when something breaks.
Cost control and reliability built into the operating model.
Review the current pipeline
We map deployment paths, eval coverage, model dependencies, observability, and the places cost can run away.
Install operating controls
Dashboards, token budgets, fallbacks, alerts, and rollback paths become part of the production system.
Operate or hand off
We can stay on retainer or leave you with runbooks, dashboards, and a clean ownership model.
For teams with real AI in production.
- →Teams with AI features already in production
- →Teams about to launch model-backed workflows
- →Companies seeing unexpected inference spend
- →Products that need eval gates, rollback paths, and observability
We fit your tooling.
Datadog, Sentry, OpenTelemetry, Grafana, and PostHog for observability. AWS and GCP, with Docker, Kubernetes, and Terraform underneath.
Production AI needs operating controls.
monitoring posture for production AI systems
Reliabilitymodel and prompt changes routed through eval gates
Quality controlper-tenant cost dashboards and token budgets
Cost controltarget path from alert to rollback decision
Incident responseRelated field notes and proof.
AI cost controls
Putting a cost ceiling on your AI before the bill puts one on you.
RAG development
Retrieval systems with eval harnesses, citations, and grounding checks.
Cloud & Infrastructure
Architecture, CI/CD, observability, and reliability foundations for production systems.