Guides, newsletters, press releases, and case studies from our team of AI engineers and researchers.
Build an AI Wealth Management Advisor using Qdrant, Gemini API, and LLMs. Enable users to query stocks, investments, and live market data with natural, human-like financial insights.
In this tutorial, learn to build trip planning system that combines the power of large language models, vector databases, and weather APIs
Learn when to use TF-IDF, BM25, SPLADE, and hybrid search, and see how Qdrant handles dense and sparse vectors side by side. Covers indexing, querying, evaluation, and best practices.
Build shopping assistants with semantic search + agents: use Qdrant, OpenAI API, Agents SDK, and Streamlit to retrieve top results, answer with context, and boost conversions—step by step.
Build hybrid data analytics agents that combine SQL + Meilisearch with LLM function calling. Handle structured queries, semantic search, and visualization in one intelligent workflow.
In this deep dive, you’ll learn how to break down the architecture, design patterns, and practical steps for building autonomous report generation agents.
Learn the difference between vector search and knowledge graphs, and why combining both powers smarter, faster, and more explainable RAG and enterprise systems.
A hands-on guide to building multiagent AI systems for manufacturing supply chain automation covering agent design, orchestration, data pipelines, and real-world deployment
This guide shows how to build a memory-powered AI agent with PostgreSQL, pgvector, Anthropic MCP, and Mistral.
In this blog, we break down how you can leverage ComfyUI’s dual-ControlNet workflow to create realistic virtual staging for real estate.
This article explores chunking strategies, implementation pipelines for evaluating them, advanced chunking methods, common implementation pitfalls, recent breakthroughs in the field
This guide explores how to use a vector database to implement efficient and accurate anomaly detection systems.
