LLMOps by CGI

Enterprises are deploying LLMs faster than they can evaluate them. Manual, fragmented testing creates bottlenecks, uneven quality standards, and gaps between offline results and real-world performance. CGI LLMOps is a model-agnostic accelerator that automates evaluation and governance across the model lifecycle, including models trained or hosted outside Databricks. Built on Mosaic AI, MLflow, and Unity Catalog, it applies a three-tier LLM-as-a-Judge architecture combining fast AI scoring, algorithmic precision metrics, and human-in-the-loop review. Continuous feedback loops route production insights back into offline evaluation, so judge accuracy improves over time. A configurable codebase, Databricks Asset Bundles, and pre-built dashboards deliver real-time visibility into quality, drift, and performance. Read our blog to learn more.

Benefits of LLMOps include:

• 4x faster model deployment through automated evaluation workflows

• 80% less manual QA effort with AI-powered quality gates

• 10x more evaluation coverage across release cycles

Note: Results from a CGI engagement with a leading U.S. telecommunications provider.