# Traccia > Traccia is an OpenTelemetry-native AI agent observability, evaluation, and governance platform for production teams. Monitor agents with real-time traces, offline cost tracking ("Sampling won't lie to you"), and policy-aware guardrails. Evaluate prompts with a versioned registry, playground, datasets, scorers, and experiments before you promote. Open-source Python SDK with integrations for LangChain, CrewAI, and OpenAI Agents. The blog covers how Traccia is building the future of AI observability, policy enforcement, and governance. Traccia provides full-fidelity tracing, EU AI Act mapping, policy alerts, and cost attribution for any LLM workload. Documentation on this site covers the Python SDK, platform dashboard, Governance Hub, integrations, and operational guides. ```bash pip install traccia ``` Sign up or log in at the Traccia app (linked from the site header) to use the hosted dashboard. ## Product - [Home](https://traccia.ai/): AI agent tracing, monitoring, and governance overview. - [Pricing](https://traccia.ai/pricing/): Plans and usage-based pricing. - [Security](https://traccia.ai/security/): Security practices and data handling. - [Trust center](https://traccia.ai/trust-center/): Vendor trust, subprocessors, and certification roadmap. - [Privacy](https://traccia.ai/privacy/): Privacy policy for Traccia and Algen AI Private Limited. - [Terms](https://traccia.ai/terms/): Terms of service for the Traccia product. - [Contact](https://traccia.ai/contact/): Support, partnerships, and company contact. - [About](https://traccia.ai/about/): Company and mission. ## Blog - [Blog](https://traccia.ai/blog/): Learn more about how Traccia is building the future of AI observability, policy enforcement, and governance. - [How to Trace OpenAI Agents with Traccia](https://traccia.ai/blog/how-to-trace-openai-agents/): Complete trace visibility into every OpenAI Agents SDK LLM call, tool invocation, and turn boundary with token counts and USD costs. - [How to Trace Gemini Agents with Traccia](https://traccia.ai/blog/how-to-trace-gemini-agents/): Gain instant visibility into every Gemini LLM call including prompts, completions, token usage, and cost with auto-instrumentation. - [Runtime Policy Enforcement in AI Agents](https://traccia.ai/blog/runtime-policy-enforcement-ai-agents/): Why AI agents need runtime policy enforcement, not just design-time guardrails: real incidents, the runtime decision flow, policy examples, the policy lifecycle, and how Traccia enforces policy in production. - [Establishing Control Boundaries for AI Agents](https://traccia.ai/blog/establishing-control-boundaries-ai-agents/): The difference between system prompt instructions and agent control plane enforcement. - [AI Agent Guardrails vs Policies](https://traccia.ai/blog/ai-agent-guardrails-vs-policies/): Guardrails shape judgement; policies constrain authority. Intent narrows authority, never grants it. - [AI Agent Cost Attribution](https://traccia.ai/blog/ai-agent-cost-attribution/): AI agent cost attribution explained: why token dashboards fail, how to attribute AI spend by agent, user, department, workflow, and business unit, and why AI governance and runtime enforcement matter as much as observability. - [Rethinking FinOps for Autonomous AI Agents](https://traccia.ai/blog/rethinking-finops-for-autonomous-ai-agents/): Traditional cloud FinOps was built for stable infrastructure. Autonomous agents demand a new discipline to track, attribute, and control dynamic costs. - [Guardrails and Policy Enforcement for OpenAI Agents](https://traccia.ai/blog/openai-agents-guardrails-policy-enforcement/): How Traccia captures OpenAI Agents SDK guardrails and enforces policy with @govern. - [What Is AI Agent Governance?](https://traccia.ai/blog/why-ai-agent-governance-became-inevitable/): Definitive guide to the four planes of control and standards mapping. - [AI Observability vs AI Governance](https://traccia.ai/blog/ai-observability-vs-ai-governance/): The fail-closed test, EchoLeak case study, and latency gap. - [Traccia vs Langfuse](https://traccia.ai/blog/langfuse-alternative/): Langfuse alternative — enforce, not just observe, with Visibility, Intelligence, Control, and Certification. - [Traccia vs Arize AI](https://traccia.ai/blog/arize-alternative/): Arize AI / Phoenix alternative focused on agent-boundary policy enforcement and EU evidence from traces. - [Traccia vs Azure AI Foundry](https://traccia.ai/blog/azure-ai-foundry-alternative/): Azure AI Foundry alternative — runtime agent enforce-and-prove on OpenTelemetry vs Azure-native model lifecycle and cloud security filters. - [Traccia vs Credo AI](https://traccia.ai/blog/credo-ai-alternative/): Credo AI alternative — runtime OpenTelemetry control plane vs enterprise GRC. - [Traccia vs Holistic AI](https://traccia.ai/blog/holistic-ai-alternative/): Holistic AI alternative — agent runtime enforce-and-prove vs portfolio GRC and bias audits. - [Traccia vs Datadog](https://traccia.ai/blog/datadog-alternative/): Datadog alternative — runtime OpenTelemetry control plane vs LLM Observability / Agent Console. - [Traccia vs Braintrust](https://traccia.ai/blog/braintrust-alternative/): Braintrust alternative — agent-boundary enforcement and EU evidence vs eval-first quality gates. - [Traccia vs LangSmith](https://traccia.ai/blog/langsmith-alternative/): LangSmith alternative — framework-agnostic control plane vs LangChain-native tracing and evals. - [Traccia vs Maxim](https://traccia.ai/blog/maxim-alternative/): Maxim alternative — enforce-and-prove on OpenTelemetry vs simulate, evaluate, and observe. ## Documentation - [Docs overview](https://traccia.ai/docs/): Entry point for the AI agent control plane: visibility, intelligence, control, and certification across the SDK and platform. - [SDK quickstart](https://traccia.ai/docs/sdk/quickstart/): Install and send your first trace in minutes. - [Platform getting started](https://traccia.ai/docs/platform/getting-started/): Set up the hosted dashboard and workspace. - [Platform OTLP ingestion](https://traccia.ai/docs/platform/ingestion/): HTTP and gRPC endpoints for SDK and native OTel clients. - [FAQ](https://traccia.ai/docs/faq/): Common questions about Traccia. - [Roadmap](https://traccia.ai/docs/roadmap/): Planned features and direction. - [Redeem a coupon code](https://traccia.ai/docs/coupon/): Log in, open Billing & Plans, and apply a coupon code to unlock a paid plan for free. ## Documentation sections - [SDK](https://traccia.ai/docs/sdk/): Index of SDK docs — decorators, prompts, evaluate(), exporters, metrics, and cost tracking. - [Platform](https://traccia.ai/docs/platform/): Index of hosted platform docs — ingestion, dashboards, guardrails, and costs. - [Concepts](https://traccia.ai/docs/concepts/): Index of core concepts — traces, spans, agents, and OpenTelemetry. - [Guides](https://traccia.ai/docs/guides/): Index of guides and recipes for tracing, experiments, multi-agent, and troubleshooting. - [Reference](https://traccia.ai/docs/reference/): Index of API, CLI, configuration, event, and error references. - [Integrations](https://traccia.ai/docs/integrations/): Index of framework integrations — LangChain, CrewAI, OpenAI Agents, and Claude Code. - [Compliance](https://traccia.ai/docs/compliance/): Index of compliance docs, including the EU AI Act and HIPAA. ## SDK - [Installation](https://traccia.ai/docs/sdk/installation/): Python package setup and requirements. - [Configuration](https://traccia.ai/docs/sdk/configuration/): Environment variables and SDK options. - [Agent identity](https://traccia.ai/docs/sdk/agent-identity/): Name and version agents in traces. - [@observe() decorator](https://traccia.ai/docs/sdk/observe-decorator/): Instrument functions and agents. - [Auto-instrumentation](https://traccia.ai/docs/sdk/auto-instrumentation/): Automatic tracing for supported frameworks. - [Exporters](https://traccia.ai/docs/sdk/exporters/): Send traces to Traccia, Jaeger, Grafana, and more. - [Metrics](https://traccia.ai/docs/sdk/metrics/): Custom metrics alongside traces. - [Governance in the SDK](https://traccia.ai/docs/sdk/governance/): observe vs govern, Preventive this-call stop, Detective next-wrap, and trace evidence. - [Guardrail detection](https://traccia.ai/docs/sdk/guardrails/): Detect policy violations in agent runs. - [Pricing and costs](https://traccia.ai/docs/sdk/pricing/): Token and cost attribution in traces. - [Prompts](https://traccia.ai/docs/sdk/prompts/): Load versioned prompts with cache, fallback, and span identity. - [Evaluate](https://traccia.ai/docs/sdk/evaluate/): Run a task and scorers over a dataset from Python or TypeScript; persist an experiment by default. - [Advanced](https://traccia.ai/docs/sdk/advanced/): Power-user SDK patterns. ## Integrations - [LangChain](https://traccia.ai/docs/integrations/langchain/): Trace LangChain chains and agents. - [Claude Code](https://traccia.ai/docs/integrations/claude-code/): Native observability for Claude Code — sessions, tool traces, and cost labels with zero code changes. - [CrewAI](https://traccia.ai/docs/integrations/crewai/): Observe CrewAI crews and tasks. - [OpenAI Agents SDK](https://traccia.ai/docs/integrations/openai-agents/): Instrument OpenAI Agents workflows. ## Platform - [OTLP ingestion](https://traccia.ai/docs/platform/ingestion/): Platform HTTP/gRPC endpoints, auth, and client-specific config. - [Dashboard](https://traccia.ai/docs/platform/dashboard/): Workspace overview and navigation. - [Traces](https://traccia.ai/docs/platform/traces/): Inspect runs, spans, and timelines. - [Guardrail posture](https://traccia.ai/docs/platform/guardrails/): Monitor guardrail health across agents. - [Policies](https://traccia.ai/docs/platform/policies/): Preventive vs Detective, Save Draft or Activate Policy, Observe / Warn / Block, Decision Log, Simulate Last 7 Days, Evaluate Now, and ingest never rejects a trace. - [Prompts](https://traccia.ai/docs/platform/prompts/): Versioned prompt library; Metrics tab (By Version, Recent Calls); Connections for agents and AI systems; promote to production with experiment evidence. - [Prompt Playground](https://traccia.ai/docs/platform/prompt-playground/): Compare prompts and models side by side with latency, tokens, and cost before you promote. - [Datasets](https://traccia.ai/docs/platform/datasets/): Curate test cases (CSV, manual, or from production traces), edit name/description, optional JSON Schema, and scorers for Prompt Playground experiments. - [Scorers](https://traccia.ai/docs/platform/scorers/): Built-in scorers, LLM-as-judge, and restricted custom code for dataset experiments. - [Experiments](https://traccia.ai/docs/platform/experiments/): Saved graded runs, runs-in-progress strip, baseline vs candidate compare (including multi-panel pairing), and evidence to attach when promoting a prompt version. - [Governance Hub](https://traccia.ai/docs/platform/governance/): Org-wide AI system registry, human review queue, incidents, audit bundles, and admin activity log. - [EU AI Act](https://traccia.ai/docs/compliance/eu-ai-act/): Opt-in module — AI system registry, human review, FRIA drafts, and labeled audit exports for EU teams. - [HIPAA](https://traccia.ai/docs/compliance/hipaa/): Opt-in module — PHI-aware registry fields, safeguard checklists, soft SDK warnings, and labeled evidence exports (no signed Traccia BAA). - [Costs](https://traccia.ai/docs/platform/costs/): Cost analytics and budgets. - [Teams](https://traccia.ai/docs/platform/teams/): Collaboration and access control. ## Concepts - [Traces](https://traccia.ai/docs/concepts/trace/): Root spans and trace structure. - [Spans](https://traccia.ai/docs/concepts/span/): Nested operations within a trace. - [Agents](https://traccia.ai/docs/concepts/agents/): How Traccia models agents. - [OpenTelemetry](https://traccia.ai/docs/concepts/opentelemetry/): OTel compatibility and semantics. ## Guides - [Local Jaeger setup](https://traccia.ai/docs/guides/local-jaeger/): Run Jaeger locally for development. - [Grafana Tempo setup](https://traccia.ai/docs/guides/local-grafana/): Export traces to Grafana Tempo. - [Multi-agent tracing](https://traccia.ai/docs/guides/multi-agent/): Trace multiple agents in one system. - [Parallel runs in one process](https://traccia.ai/docs/guides/parallel-runs/): Isolate concurrent agent runs. - [Cost optimization](https://traccia.ai/docs/guides/cost-optimization/): Reduce LLM spend with observability data. - [Run experiments from code](https://traccia.ai/docs/guides/sdk-evaluate/): Install the SDK, call evaluate(), and open the saved run under Evaluate → Experiments. - [Compare two experiments](https://traccia.ai/docs/guides/compare-experiments/): Pick a baseline and a candidate on the same dataset, then read score, cost, and latency deltas. - [Troubleshooting](https://traccia.ai/docs/guides/troubleshooting/): Fix common SDK and export issues. ## Reference - [Python SDK API](https://traccia.ai/docs/reference/python-sdk/): SDK class and method reference, including load_prompt and evaluate(). - [Node.js SDK API](https://traccia.ai/docs/reference/node-sdk/): TypeScript SDK class and method reference, including loadPrompt and evaluate(). - [CLI commands](https://traccia.ai/docs/reference/cli/): Traccia CLI usage. - [Configuration reference](https://traccia.ai/docs/reference/configuration/): Full configuration options. - [Events](https://traccia.ai/docs/reference/events/): Event types emitted by the SDK. - [Errors](https://traccia.ai/docs/reference/errors/): Error codes and handling. ## Optional - [Investor materials](https://traccia.ai/invest/): Traction, thesis, and roadmap for investors. - [Sitemap](https://traccia.ai/sitemap.xml): Machine-readable list of public URLs on this site.