LLM Ops
LLMOps (Large Language Model Operations) is the practice of building, deploying, managing, and improving applications powered by large language models (LLMs) in a reliable, scalable, and governed way.
Get StartedPrompt Management & Versioning
Treat prompts as versioned artifacts: review changes, roll back, and align templates across environments and teams.
Retrieval-Augmented Generation (RAG) Ops
Operate indexes, chunking, embedding pipelines, and freshness—so answers stay grounded and retrieval quality is measurable.
Model Orchestration, Routing & Agents Ops
Route across models and providers; run intelligent routing and Agents Ops for tool-using, multi-step workflows with guardrails and tracing.
Advanced Evaluation
Automate offline and online evals, human review loops, and gates so releases improve quality metrics you actually trust.
AI Observability & Performance
Trace requests end-to-end: latency, errors, token usage, and model outputs—so you can debug production behavior quickly.
Cost Governance & FinOps
Allocate spend by team, product, or tenant; set budgets and alerts on tokens and infrastructure before bills spike.
Guardrails & Security
Enforce content policies, PII handling, access control, and audit trails—reduce abuse and stay aligned with risk and compliance requirements.
The LLMOps Periodic Table: System Planes
Recommended process for leveraging open source, vendor-based, and native technologies.