The EU AI Act deadline is August 2, 2026, with penalties up to €15M. Here's a practical guide mapping abstract articles to concrete features ⚖️
Title: How LangSmith and LangChain OSS Help You Meet EU AI Act Requirements
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⚖️ Overview
This post explains how to meet the EU AI Act's requirements for high-risk systems using LangSmith and LangChain OSS features, mapping the articles to implementations like tracing, evaluation, and human oversight.
❓ Challenges Solved
The EU AI Act imposes strict requirements on high-risk AI. The deadline is August 2, 2026, with penalties up to €15M or 3% of global revenue. The hard part is knowing which capabilities actually satisfy the abstract articles.
💡 How It Works (articles → features)
・Observability and tracing (Article 12): end-to-end traces of LLM calls, tools, and reasoning steps; retention of 14 days (base) / 400 days (extended); EU data residency options
・Quality and safety (Article 15): online evaluators continuously score production traffic, with prebuilt evaluators for toxicity, hallucination, PII leakage, prompt injection, and more
・Human oversight (Article 14): LangGraph's interrupt for human-in-the-loop, with resume-from-exact-point recovery
・Risk management (Article 9): custom dashboards track risk scores and trigger alerts
🌍 Practical Starting Point
Build in this order — tracing → production evaluations → human-in-the-loop — and choose EU, self-hosted, or BYOC deployment based on data residency needs.
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