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News


dev.to > saaro_net > agentic-rag-2026-when-the-ai-decides-how-it-searches-9ck

Agentic RAG 2026: When the AI Decides How It Searches

1+ day, 7+ hour ago   (274+ words) Production systems standardly use LangGraph as the orchestration framework for this, supplemented by LlamaIndex for the retrieval layer. LangGraph's checkpointing makes every step of the agentic loop traceable, pausable (for human approvals), and repeatable – an essential property for compliance and…...


alphasignal.ai > news > perplexity-s-q2d-web-benchmark-tests-ai-search-on-190m-real-web-documents

Perplexity's Q2D-Web Benchmark Tests AI Search on 190M Real Web Documents

4+ day, 22+ hour ago   (291+ words) Perplexity released Q2D-Web, a large-scale benchmark with 190M documents and 70K agent-reformulated queries for evaluating retrieval in agentic RAG systems. Q2D-Web also targets a mismatch specific to agentic systems. Benchmarks typically use human-written queries, whereas RAG agents rewrite user requests into their…...


infoworld.com > article > 4220216 > databricks-unveils-adaptive-ai-retrieval-model-to-cut-search-costs-and-latency.html

Databricks unveils adaptive AI retrieval model to cut search costs and latency

5+ day, 4+ hour ago   (862+ words) Databricks on Wednesday introduced Adaptive Instructed-Retriever, a new retrieval model designed to improve enterprise AI search by taking additional steps for complex queries while stopping early on simpler ones in order to help its customers balance answer quality, latency, and…...


en.cryptonomist.ch > 09/09/2026 > databricks-ai-agent-karl

Databricks AI Agent KARL Optimizes Search Efficiency

5+ day, 7+ hour ago   (347+ words) Most artificial intelligence agents built to search for information have a habit of overdoing it — pulling context, cross-checking sources, and running searches well past the point of usefulness. Databricks decided to fix that specific problem, and the result is a…...


siliconangle.com > 09/09/2026 > databricks-adds-adaptive-search-model-to-speed-agent-retrieval

Databricks adds adaptive search model to speed agent retrieval

5+ day, 4+ hour ago   (466+ words) UPDATED 10:00 EDT / SEPTEMBER 09 2026 Databricks Inc. today expanded its Adaptive Instructed-Retriever search model to speed up response times for requests from artificial intelligence agents that require multiple rounds of retrieval. The earlier model performed parallel, single-step searches, making it fast enough…...


aithority.com > machine-learning > optivara-partners-with-frost-sullivan-to-help-organizations-strengthen-ai-visibility-and-market-perception

Optivara Partners with Frost & Sullivan to Help Organizations Strengthen AI Visibility and Market Perception

1+ week, 3+ day ago   (23+ words) Optivara announced that its AI market presence platform will power Frost & Sullivan's AI Brand Equity and Market Presence Advisory Service....


cognitiverevolution.ai > write-change-recall-forget-mongodb-s-pete-johnson-on-how-retrieval-drives-agent-performance-newsletter

Write, Change, Recall, Forget: MongoDB's Pete Johnson on How Retrieval Drives Agent Performance

1+ week, 6+ day ago   (347+ words) Hello, and welcome back to the Cognitive Revolution! Today my guest is Pete Johnson, Field CTO of AI at MongoDB. We start with a brief history of database technology, going back to the 1970 paper that gave us the relational model…...