A new ranking of vector databases for AI applications in 2026 highlights Pinecone, Weaviate, Milvus, and pgvector as top choices, evaluated on performance, scalability, ease of use, and enterprise rea…
A developer has built a RAG-powered database assistant using PostgreSQL and pgvector, enabling natural-language queries to be answered in seconds. The system retrieves schema metadata via vector simil…
An engineer at an ISP built a WhatsApp billing assistant using Corrective RAG (CRAG) and found that the main challenge was not retrieval but the model narrating correct numbers incorrectly. The system…
A 13-month experiment on a real GitLab Handbook corpus found that a RAG index grew 5x from 33,286 to 166,947 chunks, with 90% of chunks failing a ground-truth check due to ingestion bugs. The teardown…
Gartner predicts that by 2026, 40% of enterprise applications will include task-specific AI agents, up from less than 5% in 2025, as AI integration shifts from a differentiator to an operational basel…
A developer published a tutorial for building a production-grade Retrieval-Augmented Generation (RAG) API using FastAPI, pgvector, and Claude, covering document chunking, redundancy prevention, and la…
A developer is building a multi-month YouTube data workflow that uses a browser extension to capture implicit listening signals—such as skipping a track after four seconds or looping a chorus—and proc…
A developer who built CourtGPT.ai to serve 6.7M+ legal records shares 18 months of lessons on production RAG systems. Key findings include that hybrid search (BM25 + vector) achieves 92% recall at top…
Google Cloud's AlloyDB, a PostgreSQL-compatible database, now delivers up to 4x faster HNSW vector search via its columnar engine, as demonstrated by benchmarks on the GloVe 100 Angular dataset with o…
A developer built Distill.ai, an AI agent that turns messy RFQ emails into priced quotes, and deployed it on Alibaba Cloud. The system uses a seven-stage pipeline with models from Alibaba Cloud Model …
An engineer built an automated regression test suite using Pytest and Docker after a production outage caused by a missed test case during a memory storage migration from Redis to PostgreSQL with pgve…
Warden is a permission-aware retrieval and agent-authorization gateway for AI systems that enforces relationship-based, deny-aware, cross-tenant document permissions inside the retrieval path of agent…
RE-call, a retrieval-augmented generation system, introduces a benchmark that evaluates not only ranking quality but also a system's ability to abstain when no answer exists. Testing on 14 answerable …
A developer built RE-call, a retrieval-augmented memory system for AI agents that runs entirely on PostgreSQL, using pgvector for dense vector search and built-in full-text search, fused via Reciproca…
A developer proposes using a semantic cache as the primary retrieval layer in RAG systems, arguing that it can drastically reduce costs and latency by caching answers to semantically similar questions…
Eugene v0.8 introduces memory for AI agents built in Rust, shipping two complementary stores, a VectorStore trait, and agentic RAG through new skills 'remember' and 'recall'. The memory system uses ma…
A developer's tutorial explains the complete architecture of vector databases, covering schema design, indexing methods like IVF and HNSW, product quantization, distance metrics, metadata indexing, an…
A developer published a practical guide to building RAG-powered knowledge bots with Laravel and pgvector, demonstrating how to integrate custom data into LLMs to improve chatbot accuracy. Google and i…
A developer built a retrieval-augmented generation (RAG) chatbot in Laravel 11 using PostgreSQL and pgvector, storing document embeddings locally instead of relying on a vector-database SaaS. The pipe…
HNSW (Hierarchical Navigable Small World) is a graph-based algorithm that powers vector search in FAISS, pgvector, Qdrant, Weaviate, and Milvus, enabling approximate nearest neighbor search in millise…