Databricks' Instructed Retriever beats traditional RAG data retrieval by 70% — enterprise metadata was the missing link

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]

Six data shifts that will shape enterprise AI in 2026

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows.That stability eroded [...]

With 91% accuracy, open source Hindsight agentic memory provides 20/20 vision for AI agents stuck on failing RAG

It has become increasingly clear in 2025 that retrieval augmented generation (RAG) isn't enough to meet the growing data requirements for agentic AI.RAG emerged in the last couple of years to bec [...]

The AI scaffolding layer is collapsing. LlamaIndex's CEO explains what survives.

The scaffolding layer that developers once needed to ship LLM applications — indexing layers, query engines, retrieval pipelines, carefully orchestrated agent loops — is collapsing. And according [...]

The retrieval rebuild: Why hybrid retrieval intent tripled as enterprise RAG programs hit the scale wall

Something shifted in enterprise RAG in Q1 2026. VB Pulse data spanning January through March tells a consistent story: the market stopped adding retrieval layers and started fixing the ones it already [...]

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 unstructured content, sales figures alongside customer reviews or citation co [...]

Why Google’s File Search could displace DIY RAG stacks in the enterprise

By now, enterprises understand that retrieval augmented generation (RAG) allows applications and agents to find the best, most grounded information for queries. However, typical RAG setups could be an [...]

Snowflake builds new intelligence that goes beyond RAG to query and aggregate thousands of documents at once

Enterprise AI has a data problem. Despite billions in investment and increasingly capable language models, most organizations still can't answer basic analytical questions about their document re [...]

'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks

RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, thos [...]