Workflow engine where ops can yield — same async DAG handles batch jobs and event-driven streaming pipelines (pipecat-style callbot, STT → LLM → TTS). Python frontend, drop-in Rust runtime; 2–3× faster on chains, 10–30× on production workloads. LLMs, agents, RAG, native compute as first-class ops.
Trace Pi coding agent sessions with Langfuse — agent turns, model generations, token usage with cache and reasoning splits, cost, tool calls, and nested subagents.
Kubernetes operator for deploying and managing production-ready Langfuse LLM observability instances. Deploy the full stack (Web, Worker, PostgreSQL, ClickHouse, Redis, Blob Storage) from a single custom resource, with automated upgrades, secret rotation, multi-tenancy, and circuit breakers built in.
Run, watch, and meter Claude Code, Codex CLI, Gemini CLI, OpenCode, and Kiro from one CLI. Normalized events, cache-aware token usage, cost accounting verified against each agent's own records, budget caps, OpenTelemetry gen_ai spans, Langfuse traces, and a live web dashboard + MCP server.
Production-grade observability and agentic AIOps for AI systems — OpenTelemetry-native across independent polyglot apps; GenAI semantic conventions with token/cost attribution; sub-2s detection on a hot path that skips the datastore; LLM agents that find root cause and notify. ClickHouse + Langfuse. 100% self-hosted — no vendor lock-in.