AI DevOps

A working demo is not the finish line.

We operate AI like infrastructure: release control, prompt and model versioning, retrieval monitoring, cost guardrails, rollback plans, and support when business-critical automations need attention.

Why it matters

Most AI projects break quietly after launch.

🐛

Silent drift

Prompts and models change behavior over time with no one watching.

💥

No rollback

When an automation misfires, there's no version to revert to.

📈

Runaway cost

Token and API spend creep up with no guardrails or visibility.

📈

Version → test → monitor → improve.

Production discipline

The operating layer that keeps AI reliable.

  • CI/CD pipelines for AI apps, agents, prompts, and RAG configs
  • Versioning for prompts, models, and retrieval sources
  • Live monitoring for latency, errors, retrieval quality, and cost
  • Rollback plans and incident response for customer-facing systems
  • Monthly optimization reviews so systems keep improving
What we monitor

Visibility into the things that actually break.

⏱️

Latency & errors

Catch slowdowns and failures before users feel them.

🎯

Retrieval quality

Track grounding and answer quality as data and models change.

💲

Model cost

Guardrails and alerts so spend stays predictable.

Get started

Keep your AI working after launch.

We put release control, monitoring, and support around your AI systems so they stay reliable as models and data change.

30 minutes · no obligation · DFW-based team · 800-985-1365