Tag feed

#hybrid-search

15 posts0 followers

Explore Hashnode

Alternatives

Trending tags this week

SRSukalyan Roysukalyanroy.hashnode.devJun 20 · 13 min read

Adding Rank Fusion to my RAG retrieval logic

In the previous part, we explored Agentic RAG as an evolution of the traditional Retrieval-Augmented Generation pipeline:https://sukalyanroy.hashnode.dev/discovering-rags-2-what-is-agentic-rag TL;DR

0

JGJames Gainesblog.gainesai.comApr 28 · 10 min read

Why Vector Search Alone Fails on Regulatory Documents

TL;DR Vector search is great at finding semantically similar content, but it struggles with broad keyword-heavy queries common in regulatory and clinical document search. By combining BM25 keyword mat

0

CTChandre Tosca Van Der Westhuizenmindsdb.hashnode.devFeb 4 · 10 min read

How Web Apps Can Gain a Competitive Edge with Supabase and MindsDB

SaaS companies live and die by their metrics. Data is collected in operational systems, copied into warehouses, transformed through pipelines, and finally visualized in dashboards. Finance teams learn where to click. Analysts learn how to maintain th...

0

AKAnjali Kakdevectorai.hashnode.devFeb 4 · 14 min read

Vector Databases in Practice: Building a Realistic Hybrid Search RAG System with Qdrant

Vector databases are often introduced as tools for semantic similarity search. In practice, that understanding breaks down the moment you try to build a real RAG system. In this article, I explain what vector databases actually do inside modern retri...

0

CTChandre Tosca Van Der Westhuizenmindsdb.hashnode.devDec 18, 2025 · 11 min read

MariaDB & MindsDB Turns WooCommerce Data to Insights with Real-Time AI Analytics for eCommerce Teams

MariaDB is a widely used open-source relational database that powers eCommerce operations with features like high availability, scalability, and flexible storage engine options. Platforms such as WooCommerce rely on it to manage product catalogs, cus...

0

YMYash Mhaskarretrieval.hashnode.devNov 3, 2025 · 5 min read

Improving RAG Retrieval: Lessons from Building and Evaluating a Hybrid Pipeline

Introduction When I first built my retrieval pipeline, it seemed solid, a combination of dense embeddings and lexical search fused together with Reciprocal Rank Fusion (RRF).It worked well enough for most queries… until I started noticing subtle but ...

0

CTChandre Tosca Van Der Westhuizenmindsdb.hashnode.devSep 2, 2025 · 9 min read

Introducing MindsDB’s Hybrid Search: Find What Matters in a Sea of Enterprise Data

As large language models (LLMs) and vector search become increasingly common in enterprise AI stacks, one of the quiet but persistent challenges is precision. Semantic search excels at retrieving conceptually similar content, but it can fail when exa...

0

DSDhaval Singhdsdev.inAug 31, 2025 · 6 min read

Some notes on Agentic search & Turbopuffer

Search systems are always broken. Mend them with care, and like Kintsugi, they become more beautiful. Recently I’ve been diving deep in improving search & retrieval for Littlebird and here are some notes worth sharing. Turbopuffer Tpuf is an amazing...

0

AApoorvapoorv654123.hashnode.devAug 22, 2025 · 5 min read

Advanced Retrieval Augmented Generation (RAG): Scaling for Performance, Accuracy, and Real-World Readiness

Retrieval Augmented Generation (RAG) has quickly evolved from simple document lookups to sophisticated, production-grade systems. Advancing beyond basics means improving scalability, accuracy, cost, and real-world robustness using advanced retrieval,...

0

TSTanishk Sonibitphonix.hashnode.devJul 21, 2025 · 23 min read

Beyond Naive RAG: A Complete Guide to Building Production-Ready LLM Apps with Advanced Retrieval

Introduction: The RAG Hype is Real, But So Are Its Failures Retrieval-Augmented Generation (RAG) has taken the AI world by storm, promising to anchor Large Language Models (LLMs) in factual, up-to-date, and proprietary data. The concept is elegant: r...

0

#hybrid-search

Search Hashnode

#hybrid-search

Explore Hashnode

Trending tags this week

Adding Rank Fusion to my RAG retrieval logic

Why Vector Search Alone Fails on Regulatory Documents

How Web Apps Can Gain a Competitive Edge with Supabase and MindsDB

Vector Databases in Practice: Building a Realistic Hybrid Search RAG System with Qdrant

MariaDB & MindsDB Turns WooCommerce Data to Insights with Real-Time AI Analytics for eCommerce Teams

Improving RAG Retrieval: Lessons from Building and Evaluating a Hybrid Pipeline

Introducing MindsDB’s Hybrid Search: Find What Matters in a Sea of Enterprise Data

Some notes on Agentic search & Turbopuffer

Advanced Retrieval Augmented Generation (RAG): Scaling for Performance, Accuracy, and Real-World Readiness

Beyond Naive RAG: A Complete Guide to Building Production-Ready LLM Apps with Advanced Retrieval