https://techgazette.com.br/learn/rag/ New guides on rag and search, by the people who build it. Retrieval, embeddings and vector search. en 180 Wed, 14 Oct 2026 13:58:00 GMT https://aws.amazon.com/blogs/machine-learning/generate-presentations-with-amazon-bedrock-agentcore/ https://aws.amazon.com/blogs/machine-learning/generate-presentations-with-amazon-bedrock-agentcore/ Wed, 14 Oct 2026 13:58:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — This post walks you through building an AI agent system with Amazon Bedrock AgentCore that automates PowerPoint presentation creation from enterprise documents. A supervisor agent, Retrieval Augmented Generation, and Ama… https://engineering.zalando.com/posts/2026/10/structure-automating-data-ingestion-with-a-rag-flywheel.html https://engineering.zalando.com/posts/2026/10/structure-automating-data-ingestion-with-a-rag-flywheel.html Sun, 11 Oct 2026 22:00:00 GMT Zalando Engineering RAG and search Zalando Engineering — Automating schema mapping for diverse supplier data using a RAG Flywheel and LLMs. https://www.lancedb.com/blog/case-study-coderabbit https://www.lancedb.com/blog/case-study-coderabbit Sat, 10 Oct 2026 04:06:00 GMT LanceDB RAG and search LanceDB — How CodeRabbit leverages LanceDB-powered context engineering turns every review into a quality breakthrough. https://cohere.com/blog/shared-or-dedicated-inference-for-embed-rerank https://cohere.com/blog/shared-or-dedicated-inference-for-embed-rerank Fri, 09 Oct 2026 18:54:00 GMT Cohere RAG and search Cohere — Shared or dedicated AI inference? Learn how embedding and reranking workloads, traffic patterns, latency, and cost determine the right deployment choice. https://aws.amazon.com/blogs/machine-learning/icymi-what-landed-for-ai-builders-in-september-2026/ https://aws.amazon.com/blogs/machine-learning/icymi-what-landed-for-ai-builders-in-september-2026/ Fri, 09 Oct 2026 15:38:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — A monthly recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026: broader model choice, faster serverless agents with built-in evaluation, and automated knowledge base synci… https://qdrant.tech/documentation/tutorials-build-essentials/semantic-cache/ https://qdrant.tech/documentation/tutorials-build-essentials/semantic-cache/ Fri, 09 Oct 2026 08:00:00 GMT Qdrant RAG and search Qdrant — Build a Semantic Cache for a RAG Pipeline Time: 30 min Level: Intermediate What’s a Semantic Cache Traditional caches operate on an exact match basis, while semantic caches search for the meaning of the key rather… https://unity.com/blog/echo-weaver-time-loop-unity https://unity.com/blog/echo-weaver-time-loop-unity Thu, 08 Oct 2026 00:00:00 GMT Unity RAG and search Unity — Moonlight Kids explain how they built time-loop metroidbrainia Echo Weaver in Unity 6: chunk streaming, loop-reset architecture, and 2D optimization tips. https://aws.amazon.com/blogs/machine-learning/rethinking-access-control-for-rag-with-amazon-quick-and-amazon-bedrock/ https://aws.amazon.com/blogs/machine-learning/rethinking-access-control-for-rag-with-amazon-quick-and-amazon-bedrock/ Wed, 07 Oct 2026 18:34:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Enterprise RAG unlocks insights from knowledge sources like SharePoint, Google Drive, and Confluence, but those sources carry complex permissions. Learn how Amazon Quick and Amazon Bedrock Knowledge Bases enforce documen… https://www.digitalocean.com/community/tutorials/semantic-cache-verification-jev-vs-cosine-similarity https://www.digitalocean.com/community/tutorials/semantic-cache-verification-jev-vs-cosine-similarity Wed, 07 Oct 2026 11:00:00 GMT DigitalOcean Tutorials RAG and search DigitalOcean Tutorials — We tested cosine similarity, prompted LLMs, and a purpose-built verifier (Jev) on 500 labeled query pairs, and cosine was clearly the least accurate, serving near-misses like "capital of Kenya" for "capital of Jamaica."… https://posthog.com/blog/wtf-is-context-engineering https://posthog.com/blog/wtf-is-context-engineering Wed, 07 Oct 2026 00:00:00 GMT PostHog RAG and search PostHog — Say you're deploying an AI assistant that processes online order returns. For it to work, it would need access to your store's purchase policy, item… https://pytorch.org/blog/modernizing-table-batched-embeddings-with-fbtriton/ https://pytorch.org/blog/modernizing-table-batched-embeddings-with-fbtriton/ Tue, 06 Oct 2026 22:57:00 GMT PyTorch RAG and search PyTorch — This post explores the FBTriton kernel design for Table Batched Embedding (TBE) forward and backward passes. These core operators handle embedding lookups across thousands of sharded GPUs within recommendation systems...… https://aws.amazon.com/blogs/machine-learning/build-a-voice-travel-concierge-with-amazon-bedrock-agentcore-managed-knowledge-base-and-nova-sonic/ https://aws.amazon.com/blogs/machine-learning/build-a-voice-travel-concierge-with-amazon-bedrock-agentcore-managed-knowledge-base-and-nova-sonic/ Tue, 06 Oct 2026 15:45:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Add a voice travel concierge to an airline app with Amazon Bedrock AgentCore, Amazon Nova Sonic for real-time speech, and Amazon Bedrock Knowledge Bases for policy answers. Travelers change seats, check delays, and ask p… https://www.akamai.com/blog/ai/2026/oct/vector-search-cant-tell-yes-from-no https://www.akamai.com/blog/ai/2026/oct/vector-search-cant-tell-yes-from-no Tue, 06 Oct 2026 13:00:00 GMT Akamai Cloud (Linode) RAG and search Akamai Cloud (Linode) — Learn why vector search can rank contradictory statements as similar, and how hybrid retrieval can help RAG systems identify conflicting information. https://developers.googleblog.com/embeddinggemma-2-the-developer-guide/ https://developers.googleblog.com/embeddinggemma-2-the-developer-guide/ Tue, 06 Oct 2026 00:00:00 GMT Google for Developers RAG and search Google for Developers — EmbeddingGemma 2 is a compact, open-source multimodal embedding model that maps text, code, images, video, and audio into a unified 768-dimensional space. Developers can use the sentence-transformers library to selective… https://www.thoughtworks.com/insights/blog/generative-ai/how-jev-can-help-improve-the-efficiency-of-rag-pipelines https://www.thoughtworks.com/insights/blog/generative-ai/how-jev-can-help-improve-the-efficiency-of-rag-pipelines Tue, 06 Oct 2026 00:00:00 GMT Thoughtworks RAG and search Thoughtworks — How Jev can help improve the efficiency of RAG pipelines https://www.databricks.com/blog/nearest-join-scaling-vector-search-databricks-runtime https://www.databricks.com/blog/nearest-join-scaling-vector-search-databricks-runtime Mon, 05 Oct 2026 20:00:00 GMT Databricks RAG and search Databricks — Vector search originated as a serving problem. The classical use case is a chatbot... https://aws.amazon.com/blogs/machine-learning/making-amazon-quick-enterprise-ready-automated-auditable-cross-account-resource-promotion/ https://aws.amazon.com/blogs/machine-learning/making-amazon-quick-enterprise-ready-automated-auditable-cross-account-resource-promotion/ Mon, 05 Oct 2026 15:56:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Promoting Amazon Quick resources (agents, action connectors, knowledge bases, flows, and spaces) from a development to a production AWS account has been a manual, error-prone chore. This post shows how to automate cross-… https://aws.amazon.com/blogs/machine-learning/agentic-retrieval-with-langchain-and-amazon-bedrock-knowledge-bases/ https://aws.amazon.com/blogs/machine-learning/agentic-retrieval-with-langchain-and-amazon-bedrock-knowledge-bases/ Mon, 05 Oct 2026 15:53:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Build a Retrieval Augmented Generation (RAG) application on Amazon Bedrock Managed Knowledge Base with LangChain, and see how agentic retrieval handles the multi-part questions that single-shot retrieval answers poorly.… https://spring.io/blog/2026/10/02/spring-ai-modular-rag-typesafe-jev https://spring.io/blog/2026/10/02/spring-ai-modular-rag-typesafe-jev Fri, 02 Oct 2026 00:00:00 GMT Spring RAG and search Spring — Spring AI: RAG Doc | Jev Doc | Demo In the previous article we introduced Spring AI TypeSafe and its Jev model: typed questions in, calibrated numbers out, in a few hundred milliseconds. One row in that article's SPI tab… https://www.lancedb.com/blog/how-jev-compares-to-other-rerankers https://www.lancedb.com/blog/how-jev-compares-to-other-rerankers Thu, 01 Oct 2026 03:58:00 GMT LanceDB RAG and search LanceDB — See how Jev performs in a benchmark of 19 reranker configurations across five datasets, covering accuracy, latency, and prompt-driven relevance for LanceDB search. https://neo4j.com/blog/agentic-ai/contextual-retrieval/ https://neo4j.com/blog/agentic-ai/contextual-retrieval/ Wed, 30 Sep 2026 19:14:00 GMT Neo4j RAG and search Neo4j — Most RAG systems today score how semantically similar a new query is to stored text chunks and return a list of the best matches. However, information doesn’t need to include similar words to be relevant. Data entities m… https://aws.amazon.com/blogs/machine-learning/query-claims-in-natural-language-with-amazon-bedrock-knowledge-bases/ https://aws.amazon.com/blogs/machine-learning/query-claims-in-natural-language-with-amazon-bedrock-knowledge-bases/ Wed, 30 Sep 2026 15:37:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon S3, querying with t… https://neon.com/blog/lakebase-search-retrieval-agents https://neon.com/blog/lakebase-search-retrieval-agents Wed, 30 Sep 2026 12:00:00 GMT Neon RAG and search Neon — Build the search engine, ingestion layer, and serving layer for agent retrieval with Lakebase Search, Functions, Object Storage, and AI Gateway. https://www.pingcap.com/blog/vector-and-full-text-search-for-ai-agents/ https://www.pingcap.com/blog/vector-and-full-text-search-for-ai-agents/ Wed, 30 Sep 2026 00:03:00 GMT PingCAP (TiDB) RAG and search PingCAP (TiDB) — Key Takeaways Ask an AI support agent about error E-4012 and it may come back with a confident answer about E-4021. The embeddings for the two codes sit almost on top of each other, so the agent pulled the wrong runbook,… https://www.elastic.co/search-labs/blog/ecommerce-search-reranking-llm-alternative-jev https://www.elastic.co/search-labs/blog/ecommerce-search-reranking-llm-alternative-jev Wed, 30 Sep 2026 00:00:00 GMT Elasticsearch Labs RAG and search Elasticsearch Labs — We had Jev score Elasticsearch hybrid search results and let a short Python policy do the reranking, taking nDCG@10 from 0.9351 to 0.9565 on 250 Amazon Shopping Queries, and the code is all here. https://aws.amazon.com/blogs/machine-learning/building-an-ai-powered-contract-intelligence-platform-with-amazon-quick-and-amazon-bedrock-agentcore/ https://aws.amazon.com/blogs/machine-learning/building-an-ai-powered-contract-intelligence-platform-with-amazon-quick-and-amazon-bedrock-agentcore/ Tue, 29 Sep 2026 16:14:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses AI agents to extract… https://turbopuffer.com/blog/native-embedding https://turbopuffer.com/blog/native-embedding Tue, 29 Sep 2026 00:00:00 GMT turbopuffer RAG and search turbopuffer — Native embedding isn't just a convenience feature, but a way to shave hundreds of milliseconds off your search queries. https://www.percona.com/blog/when-pt-online-schema-change-where-meets-galera-understanding-chunk-auto-resize-and-flow-control/ https://www.percona.com/blog/when-pt-online-schema-change-where-meets-galera-understanding-chunk-auto-resize-and-flow-control/ Mon, 28 Sep 2026 13:56:00 GMT Percona RAG and search Percona — Percona Toolkit’s pt-online-schema-change (pt-osc) has long been the preferred solution for performing online schema changes with minimal downtime. Its chunk-based copy algorithm is designed to adapt dynamically to the w… https://www.lancedb.com/blog/how-jev-compares-to-other-rerankers-for-lancedb-search https://www.lancedb.com/blog/how-jev-compares-to-other-rerankers-for-lancedb-search Sat, 26 Sep 2026 06:41:00 GMT LanceDB RAG and search LanceDB — See how Jev compares with 19 reranker configurations across five datasets on accuracy, latency, and prompt-driven relevance for LanceDB search. https://www.pinecone.io/learn/hybrid-search-postgres-pinecone/ https://www.pinecone.io/learn/hybrid-search-postgres-pinecone/ Fri, 25 Sep 2026 20:38:00 GMT Pinecone RAG and search Pinecone — Add hybrid search to a Postgres app with Pinecone: full-text and vector search in one index, Postgres as the source of truth. Built around a snack shop example. https://rocm.blogs.amd.com/artificial-intelligence/model-weight-profiles/README.html https://rocm.blogs.amd.com/artificial-intelligence/model-weight-profiles/README.html Fri, 25 Sep 2026 00:00:00 GMT AMD ROCm RAG and search AMD ROCm — This blog describes model weight profiles, which show how many model parameters are devoted to embeddings, attention, dense layers, and other components, and in which number formats. That split can be used to calculate t… https://www.getdbt.com/blog/context-engineering-in-your-warehouse https://www.getdbt.com/blog/context-engineering-in-your-warehouse Thu, 24 Sep 2026 15:57:00 GMT dbt Labs RAG and search dbt Labs — Analytics teams have always modeled data for BI. Context engineering models data for agents, starting with semantic search. https://www.elastic.co/blog/atomic-claim-checking-against-llm-hallucinations https://www.elastic.co/blog/atomic-claim-checking-against-llm-hallucinations Thu, 24 Sep 2026 00:00:00 GMT Elastic RAG and search Elastic — Hallucinations kept an LLM out of our knowledge base cleanup for years. Splitting generation from atomic claim verification fixed it and cleared a four-year backlog of duplicate articles. https://newrelic.com/blog/observability/how-to-build-an-sre-agent-that-actually-works-without-blowing-the-token-budget https://newrelic.com/blog/observability/how-to-build-an-sre-agent-that-actually-works-without-blowing-the-token-budget Tue, 22 Sep 2026 12:00:00 GMT New Relic RAG and search New Relic — Learn how to build an SRE agent that delivers accurate, low-latency incident triage with multi-tiered memory and RAG—without blowing your token budget. https://weaviate.io/blog/engram-memory-practical-guide https://weaviate.io/blog/engram-memory-practical-guide Tue, 22 Sep 2026 00:00:00 GMT Weaviate RAG and search Weaviate — Learn how to use Engram effectively, from writing topic descriptions that control extraction to choosing bounded topics and scopes, selecting a retrieval mode, and placing memories in your prompt without hurting prompt-c… https://planetscale.com/blog/anatomy-of-a-postgres-search-engine https://planetscale.com/blog/anatomy-of-a-postgres-search-engine Tue, 22 Sep 2026 00:00:00 GMT PlanetScale RAG and search PlanetScale — How a full-text search engine works, and how it works in Postgres https://aws.amazon.com/blogs/machine-learning/migrating-multi-model-ai-agents-to-amazon-bedrock-agentcore-runtime/ https://aws.amazon.com/blogs/machine-learning/migrating-multi-model-ai-agents-to-amazon-bedrock-agentcore-runtime/ Fri, 18 Sep 2026 15:38:00 GMT AWS Machine Learning RAG and search AWS Machine Learning — Migrate a multi-model healthcare AI agent from self-managed Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, preserving triple-model orchestration and vector-enhanced knowledge retrieval while reducing in… https://blog.jetbrains.com/ai/2026/09/building-a-rag-pipeline-for-semantic-code-search-a-developer-diary-and-field-notes/ https://blog.jetbrains.com/ai/2026/09/building-a-rag-pipeline-for-semantic-code-search-a-developer-diary-and-field-notes/ Thu, 17 Sep 2026 12:39:00 GMT JetBrains AI RAG and search JetBrains AI — Part 1: Parsing, chunking, and vectorization Some time ago, we set out to build the best semantic code search platform we could: a RAG pipeline that gives LLM agents precise, citable evidence from real repositories inste… https://wandb.ai/ai-team-articles/llm-evaluation/reports/RAG-pipeline-tutorial-Common-pitfalls-and-how-to-fix-them---VmlldzoxNzE2MTA0OA https://wandb.ai/ai-team-articles/llm-evaluation/reports/RAG-pipeline-tutorial-Common-pitfalls-and-how-to-fix-them---VmlldzoxNzE2MTA0OA Mon, 14 Sep 2026 04:19:00 GMT Weights & Biases RAG and search Weights & Biases — RAG tutorial: build a LangChain Q&A pipeline over your docs—chunking, embeddings, retrieval, citations, and Weave evaluation, pitfalls fixed. https://medium.com/pinterest-engineering/evolving-pinterests-embedding-retrieval-platform-aede4e831e01?source=rss----4c5a5f6279b6---4 https://medium.com/pinterest-engineering/evolving-pinterests-embedding-retrieval-platform-aede4e831e01?source=rss----4c5a5f6279b6---4 Fri, 11 Sep 2026 15:01:00 GMT Pinterest Engineering RAG and search Pinterest Engineering — Authors: Bowen Zhou | Staff Software Engineer; Shan Gao | Senior Software Engineer; Jingwen Hu | Software Engineer II; Wenjiang Chu | Staff Software Engineer The Billion-Embedding Challenge At Pinterest, the “signal” is…