AI Agent Observability
AI agent observability answers three questions for every run: what did it cost, how long did it take, and what did it actually do? agentFast records all of it as a structured step tree — so you can prove ROI, debug a failure, and catch a cost regression before it hits a bill.
Every run is a step tree
An ordered tree of LLM calls, tool calls, memory recalls, guardrail interventions and HITL pauses — rendered in the dashboard.
Cache-aware cost accounting
Per-step cost against a configurable pricing table, counting prompt-cache reads and writes separately — the line item that dominates long runs.
Canonical telemetry record
Each run rolls up: complexity, total cost, cache tokens, LLM vs tool latency, tool errors, guardrail interventions, PII redactions and eval outcome.
OpenTelemetry export
Full span-tree export to any OTLP backend, with deterministic span timing and attributes.
First-class LangSmith
A real LangSmith exporter following its project/api-key conventions — not just a generic OTLP endpoint.
Redacted by construction
Traces are written after the guardrail pipeline, so PII never lands in a stored span in the clear.
Observability pairs with evals to turn a prompt change from a gamble into a measurement, and with guardrails so every intervention is a visible step. It ships on every SDK — start with the OpenAI Agents SDK or LangGraph.
agentFast is the production layer — memory, 50 tools, observability, evals, guardrails, human-in-the-loop — for LangGraph, CrewAI, the Claude & OpenAI Agent SDKs & Vanilla. Own it for life.
Get agentFast — from $89