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Introduction

Introduction

AITracer documentation for traceability, governance, verification, and AI cost visibility.

AITracer is the visibility layer for production AI calls. It turns black-box LLM and agent executions into secure, auditable, and cost-aware records.

The product identity comes from the original trace explorer experience:

  • Prove every response with canonical records and SHA-256 integrity hashes.
  • Track every penny with token usage, model distribution, and action-level cost.
  • Secure every prompt with high-risk heuristics and governance policy results.
  • Monitor performance with P95 latency and anomaly signals.

AITracer is designed for enterprise governance, observability, and verification across modern AI systems.

Documentation scope: how to integrate your apps and models, call the HTTP APIs, use SDKs, and apply common self-hosted or cloud deployment patterns. It does not describe vendor-internal hosting topology, operational secrets, or proprietary infrastructure diagrams.

Where to start

Terminology

Learn the core economics, vault, intelligence, and lifecycle terms used across AITracer.

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Quick Start

Connect your first provider, submit traces, and confirm governance and verification outcomes.

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First Trace

Capture a complete trace lifecycle and validate what your team will monitor in production.

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