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Bayer and Thoughtworks Ship PRINCE Agentic RAG Platform

Bayer and Thoughtworks Ship PRINCE Agentic RAG Platform

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 HN AI Security

Bayer AG and Thoughtworks have published a detailed case study on PRINCE, a production agentic RAG system combining multi-agent orchestration, Text-to-SQL, and human-in-the-loop workflows to answer complex pharmaceutical preclinical research questions and draft regulatory documents. The system's architecture — spanning intent clarification, planning, retrieval, reflection, and writing agents with access to decades of safety study data — introduces a broad attack surface including prompt injection across agent boundaries, SQL injection via natural language, and sensitive data exfiltration through compromised agent outputs. Defenders evaluating similar agentic platforms should treat each inter-agent handoff as a trust boundary requiring independent validation and focus on data leakage controls given the sensitivity of preclinical regulatory data.

GitHub Ships Data Analytics Agent Built on Copilot

GitHub Ships Data Analytics Agent Built on Copilot

FIRST LOOK ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.8 GitHub Blog

GitHub has published a detailed engineering account of how it built an internal data analytics agent using GitHub Copilot, exposing the architectural patterns — including natural language-to-SQL translation, autonomous tool invocation, and internal data access — that underpin such systems. For defenders, this blueprint highlights concrete risks around prompt injection into analytics pipelines, excessive agency over sensitive internal datasets, and the challenge of auditing LLM-generated queries before execution. Organisations adopting similar agentic analytics patterns should treat this as a reference threat model rather than a safe-to-copy architecture.

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