# Traccia: An OpenTelemetry-Based Governance Platform for AI Systems

arXiv: https://arxiv.org/abs/2607.14309 · HTML: https://mlsanity.com/paper/2607.14309/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 88 references that are in the map.
- First posted on arXiv 15 Jul 2026.

## Builds on (most cited first, 28 of 28)

- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Auditing large language models: a three-layered approach](https://mlsanity.com/paper/2302.08500/) (2023)
- [The Ethics of AI Ethics -- An Evaluation of Guidelines](https://mlsanity.com/paper/1903.03425/) (2019)
- [Probing and Steering Evaluation Awareness of Language Models](https://mlsanity.com/paper/2507.01786/) (2025)
- [Building Ethics into Artificial Intelligence](https://mlsanity.com/paper/1812.02953/) (2018)
- [Aligned with Whom? Direct and social goals for AI systems](https://mlsanity.com/paper/2205.04279/) (2022)
- [Bridging the Gap in XAI-Why Reliable Metrics Matter for Explainability and Compliance](https://mlsanity.com/paper/2502.04695/) (2025)
- [Interactional Fairness in LLM Multi-Agent Systems: An Evaluation Framework](https://mlsanity.com/paper/2505.12001/) (2025)
- [Integrating Traditional Technical Analysis with AI: A Multi-Agent LLM-Based Approach to Stock Market Forecasting](https://mlsanity.com/paper/2506.16813/) (2025)
- [False Sense of Security in Explainable Artificial Intelligence (XAI)](https://mlsanity.com/paper/2405.03820/) (2024)
- [The Unified Control Framework: Establishing a Common Foundation for Enterprise AI Governance, Risk Management and Regulatory Compliance](https://mlsanity.com/paper/2503.05937/) (2025)
- [Mapping Human Anti-collusion Mechanisms to Multi-agent AI Systems](https://mlsanity.com/paper/2601.00360/) (2026)
- [Timing and Memory Telemetry on GPUs for AI Governance](https://mlsanity.com/paper/2602.09369/) (2026)
- [AI Trust OS -- A Continuous Governance Framework for Autonomous AI Observability and Zero-Trust Compliance in Enterprise Environments](https://mlsanity.com/paper/2604.04749/) (2026)
- [Detecting Hidden ML Training With Zero-Overhead Telemetry](https://mlsanity.com/paper/2606.19262/) (2026)
- [Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications](https://mlsanity.com/paper/2506.10467/) (2025)
- [Interpretability as Alignment: Making Internal Understanding a Design Principle](https://mlsanity.com/paper/2509.08592/) (2025)
- [Reproducibility: The New Frontier in AI Governance](https://mlsanity.com/paper/2510.11595/) (2025)
- [Who Governs the Machine? A Machine Identity Governance Taxonomy (MIGT) for AI Systems Operating Across Enterprise and Geopolitical Boundaries](https://mlsanity.com/paper/2604.06148/) (2026)
- [Making AI Compliance Evidence Machine-Readable](https://mlsanity.com/paper/2604.13767/) (2026)
- [Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration](https://mlsanity.com/paper/2604.21554/) (2026)
- [AI Governance in the Context of the EU AI Act: A Bibliometric and Literature Review Approach](https://mlsanity.com/paper/2502.03468/) (2025)
- [One Bad NOFO? AI Governance in Federal Grantmaking](https://mlsanity.com/paper/2505.08133/) (2025)
- [A Taxonomy for Design and Evaluation of Prompt-Based Natural Language Explanations](https://mlsanity.com/paper/2507.10585/) (2025)
- [MALTopic: Multi-Agent LLM Topic Modeling Framework](https://mlsanity.com/paper/2601.15299/) (2026)
- [AI Governance Control Stack for Operational Stability: Achieving Hardened Governance in AI Systems](https://mlsanity.com/paper/2604.03262/) (2026)
- [Operational AI Deployment Assurance: Governance-State Orchestration Under Threshold-Sensitive Deployment Conditions -- A Governance Framework for High-Stakes AI Systems](https://mlsanity.com/paper/2605.27827/) (2026)
- [The AI Legal Specialist: A Juridically Autonomous Professional Profile for AI Governance](https://mlsanity.com/paper/2606.12415/) (2026)

## Built on by (most cited first, 1 of 1)

- [AgentStripes: An Evidence-Graded Maturity Model for AI Agents](https://mlsanity.com/paper/2610.18603/) (2026)

## Abstract (arXiv)

The rapid development of Large Language Models (LLMs) and Artificial Intelligent (AI) powered autonomous agents has fundamentally changed the existing forms of software governance. In spite of the rigorous standards of transparency and account ability required according to the international frameworks such as the European Union's AI Act, there is a considerable gap between theory and reality. The present study discusses the inherent drawbacks of currently utilized platforms for LLM evaluation, machine learning workflow, and application performance monitoring in general. It has been shown that current disjointed solutions fail to protect unbound state space agentic architecture from serious threats such as alignment drift, SaaS security concerns, and unauthorized deployment of shadow AI systems. Moreover, a solution is proposed for overcoming the discussed challenges in form of a coherent multi-level AI governance stack Traccia built on the top of OpenTelemetry infrastructure platform. Traccia resolves the last mile for AI Alignment by adding the telemetry data, passive semantic guardrail assessment, and execution lineage into a hashed trace ledger. Traccia automatically creates compliance evidence packages by appending tamper-resistant fingerprints and SHA-256 content hash, that map to regulatory requirements (Articles 12, 14, 19, 26(6), and 50 of the EU AI Act) without invading any data privacy. By performing this evaluation in a methodical manner, a solid machine-readable base has been created for enterprise-wide management of autonomous AI systems.