Data & AI

Model Context Protocol (MCP) solves the real bottleneck in enterprise AI by standardizing how AI systems connect to tools, data and workflows. When combined with Progress Agentic RAG, it transforms retrieval into a reusable, governed capability, enabling AI agents to access trusted knowledge, compare sources and deliver grounded, traceable answers across multiple systems.

Agentic RAG can help you build a company knowledge assistant so you can use actual data from your company. Here’s a practical guide for how to get started.

ICYMI: Eudald Camprubí on retrieval-augmented generation, small language models and secure AI adoption.

This blog argues that the success of a retrieval-augmented generation (RAG) system depends more on data quality, metadata and governance than on model tuning or pipeline optimization. Without clear metadata, document ownership, permissions and freshness controls, AI systems can retrieve outdated or incorrect information, leading to hallucinations. Ultimately, trustworthy AI requires well-structured, governed data, not just more advanced models.