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List of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search
High performance and CommonMark compliant HTML to Markdown converter. Maintained by the Kreuzberg team. Kreuzberg is a fast, polyglot document intelligence engine with a Rust core. It extracts structured data from 56+ document formats using streaming parsers and built-in OCR.
Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.
Use LLMs for building real-world apps
True on-device AI for Kotlin Multiplatform (Android, iOS, Desktop, JVM, WASM). LLM, Speech-to-Text and Image Generation — powered by llama.cpp, whisper.cpp and stable-diffusion.cpp.
🤖🔎 STREAM: Search with Top Result Extraction & Answer Model 🔤📊 SEEKTOPIC 🚜📜 Tractor the Text Extractor 📈📝 REASON Docs Writing Agent
Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)
Medical RAG QA App using Meditron 7B LLM, Qdrant Vector Database, and PubMedBERT Embedding Model.
"Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases" by Jiarui Li and Ye Yuan and Zehua Zhang
'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker
Quickfire is an insurance AMS built for P&C teams, independent agencies, wholesalers, and brokers. It’s designed to seamlessly integrate third-party APIs, support customizable workflows, and provide agentic AI tools that streamline both renewals and new business. Quickfire delivers true desktop-grade speed on the blazing-fast Blazor framework.
A proof-of-concept for a RAG to query the scikit-learn documentation
End-to-end financial text-analysis using Bigdata API and the Bigdata-Research-Tools library. Ready-to-use notebooks with RAG & GenAI enabling thematic and risk screening, trend tracking, and automated report generation, extracting insights at scale.
Anthropic's Contextual Retrieval implementation with visual chunk comparison. Preview context enrichment before/after embedding.
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