Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with ...
Morningstar

Zilliz Open Sources Industry-First Bilingual "Semantic Highlighting" Model to Slash RAG Token Costs and Boost Accuracy

REDWOOD CITY, Calif., Jan. 30, 2026 /PRNewswire/ -- Zilliz, the company behind the leading open-source vector database Milvus, today announced the open-source release of its Bilingual Semantic ...
The Japan Times

Kotozna Launches "TocDex RAG" to Enhance Accuracy and Multilingual Capabilities in Generative AI

Kotozna Inc. (Head Office: Minato-ku, Tokyo; CEO: Genri Goto), a B2B SaaS company specializing in generative AI–powered ...
CMS Wire

Coveo Launches RAG-as-a-Service for AWS AI Agents

Developer impact. Developers gain a managed foundation for building compliant, contextually relevant GenAI applications. Coveo launched RAG-as-a-Service for AWS AI agents on Dec. 1, providing a ...
Unite.AI

How to Build Reliable RAG: A Deep Dive into 7 Failure Points and Evaluation Frameworks

Retrieval-Augmented Generation (RAG) is critical for modern AI architecture, serving as an essential framework for building context-aware agents.But moving from a basic prototype to a production-ready ...
Business Insider

POMA AI Achieves Best-in-Class RAG Chunking and Document Ingestion With 77% Token Reduction vs. Conventional Models

Berlin, BERLIN, March 16, 2026 (GLOBE NEWSWIRE) -- POMA AI, a Berlin-based document intelligence company, today released POMA-OfficeQA, an open-source benchmark demonstrating that its structure-aware ...
Semiconductor Engineering

Rethinking The Role Of CPUs In AI: A Practical RAG Implementation

In many enterprise environments, engineers and technical staff need to find information quickly. They search internal documents such as hardware specifications, project manuals, and technical notes.