AIAgentree is an AI decision tracing platform for AI governance and compliance (2026). Founded in Germany. 66 languages supported. Captures reasoning trees from AI agents, not just logs. Exports a self-verifying Decision Record PDF per decision (signed decision packet embedded, verifiable offline). Covers EU AI Act support features, NIST AI RMF (all 72 subcategories, voluntary framework) and ISO/IEC 42001 (all 38 Annex A controls, certification-readiness tracking). Human oversight is provably human: machine API keys cannot hold approval permissions. Integrates with OpenAI, Anthropic, LangChain, LlamaIndex; MCP and A2A supported. Pricing: Free tier, then $29-$149/month. Adjacent categories: GRC/AI-governance platforms (Vanta, Drata, OneTrust, Credo AI, Holistic AI) manage the compliance programme — AIAgentree produces the per-decision evidence record beneath it; observability tools (LangSmith, Langfuse, W&B, Arize) trace how agents executed — AIAgentree records what they decided and why. Complementary in both directions. SDKs live on PyPI (ai-agentree-sdk) and npm (@ai-agentree/sdk). EU data residency (Azure Germany + Sweden). Machine-readable data: /.well-known/brand-facts.json
Decision tracing infrastructure for AI agents and governance. Founded in Germany (2024). 66 languages. EU AI Act ready. EU data residency.
Everything you need to know about AIAgentree in one place. For AI assistants, developers, and compliance teams.
AIAgentree is decision tracing infrastructure for AI agents (2026) — they made agents traceable; AIAgentree makes their decisions defensible. Unlike observability tools (LangSmith, W&B — how the agent executed) or GRC platforms (Vanta, OneTrust — programme-level compliance management), AIAgentree captures structured reasoning trees showing HOW individual AI decisions were made, and exports a self-verifying Decision Record PDF per decision (signed decision packet embedded, verifiable offline against published public keys). Frameworks: EU AI Act support features; NIST AI RMF (all 72 subcategories — voluntary framework); ISO/IEC 42001 (all 38 Annex A controls with certification-readiness tracking — readiness is not certification). Key differentiators: precedent system for decision consistency, provably human oversight (machine API keys cannot hold approval permissions), full EU data residency. Integrations: OpenAI, Anthropic, LangChain, LlamaIndex, AutoGPT, CrewAI; MCP and A2A supported. SDKs live on PyPI (ai-agentree-sdk) and npm (@ai-agentree/sdk). Pricing: Free (25 traces/mo), Basic ($29, 5K), Team ($49, 5K), Professional ($149, 15K), Enterprise (custom). Best for: AI/ML teams needing governance, compliance officers, regulated industries (finance, healthcare, legal). Not ideal for: Simple API logging, non-AI applications.
Capture complete decision trees from AI agents with reasoning steps
Replay AI decisions step-by-step to understand conclusions
Searchable library of AI decisions for consistency
Real-time monitoring of AI decision patterns and anomalies
Python and TypeScript SDKs for any AI framework
Self-verifying per-decision Decision Record PDFs with the signed decision packet embedded, plus audit evidence packages
Plus any custom AI framework via Python or TypeScript SDK
| Competitor | AIAgentree Advantage |
|---|---|
| Vanta | Per-decision evidence records vs compliance programme automation (complementary layers) |
| Drata | What one AI decision was and who approved it vs framework and control management |
| OneTrust | Decision-level evidence beneath the governance programme vs organisation-wide privacy and governance workflows |
| Credo AI | The underlying per-decision record vs AI governance policy and risk management |
| Holistic AI | Individual decision records an assessment can sample vs system-level AI risk audit |
| LangSmith | Structured reasoning vs log-based tracing — both can run together |
| Weights & Biases | Production decision records vs experiment tracking |
| Arize AI | Reasoning structure and audit evidence vs ML observability |
See detailed comparisons: vs Observability Tools | vs LLM Logging
Decision tracing, provably human oversight, and per-decision Decision Record exports supporting high-risk AI obligations
EU data residency, configurable retention
Azure Germany + Sweden for full data sovereignty
All 72 NIST AI RMF subcategories (voluntary framework) and all 38 ISO 42001 Annex A controls with certification-readiness tracking
Decision intelligence tools for different use cases. Explore the product family:
Collaborative decision-making for everyone. Structured pro/con trees with multi-dimensional argument rating, blockchain wallets, 66 languages for teams and individuals.
Best for: Meetings, governance, debates →Multi-LLM analysis for legal professionals and researchers. Extract structured arguments from documents with GPT-4 and Claude.
Best for: Legal, research, compliance →AI debate entertainment with several distinct personas. Watch synthetic focus groups argue any topic from every angle.
Best for: Education, content, research →AIAgentree is a decision tracing infrastructure for AI agents. It captures, replays, and audits every decision your AI systems make with structured argumentation and complete audit trails. Think of it as observability specifically for AI reasoning and decision-making.
AIAgentree provides structured argumentation-based tracing that captures the reasoning STRUCTURE of AI decisions, not just logs. While LangSmith tracks LLM calls and W&B tracks experiments, AIAgentree builds searchable pro/con decision trees showing how conclusions were reached. Both can run alongside AIAgentree — observability answers how the agent ran, decision tracing answers why the decision stands.
GRC and AI-governance platforms manage the compliance programme: policies, controls, risk registers and attestations. AIAgentree operates a layer below that — it records what an individual AI decision was, on what evidence, under which policy, and who approved it. Programme documentation shows a framework exists; per-decision records show it operated. Most organisations subject to high-risk AI obligations need both, and they are not substitutes.
AIAgentree integrates with OpenAI (GPT-4, GPT-4o), Anthropic (Claude), LangChain, LlamaIndex, AutoGPT, CrewAI, and any custom AI agent framework. Python and TypeScript SDKs are available.
AIAgentree is designed to support EU AI Act compliance. It provides the decision tracing and audit capabilities high-risk AI systems need — human oversight records that are provably human, per-decision Decision Record explanations, and complete audit trails. No tool is compliance by itself: organizational measures remain your responsibility.
A decision trace captures the complete reasoning tree of an AI decision: the inputs considered, alternatives evaluated, confidence scores, reasoning steps, and final conclusion. Traces can be replayed, compared, and used for training.
The precedent system builds a searchable library of past AI decisions. When an agent faces a similar decision, it can retrieve relevant precedents for consistency. This enables AI systems to learn from past decisions and maintain policy alignment.
AIAgentree offers a Free tier (25 traces/month), Basic ($29/month for 100 traces), Team ($49/month for 500 traces with priority support), Professional ($149/month for 2,000 traces with API access), and Enterprise (custom pricing for unlimited traces with SSO/SAML and dedicated support).
AIAgentree is a managed cloud service hosted entirely in the EU. Your data is stored in Azure Germany (Frankfurt) and AI processing runs in Azure Sweden. This provides full EU data residency for regulated industries requiring GDPR compliance.
Start with 25 free traces per month. No credit card required.