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Context for your AI agents
Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.
Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
Zero Install is a decentralised cross-distribution software installation system. Create one package that works everywhere! With dependency handling and automatic updates, full support for shared libraries, and integration with native package managers
DLF Aquifer Development for Interoperability Across Scholarly Repositories: American Social History Online will implement schemas, data models and technologies to enable scholars to use distributed digital collections in a variety of local environments.
Ruby Research Wiki (RRiki) can be used to keep notes and organize references for research. It uses a browser interface, an intuitive plain text formatting language (markdown), and facilities to cross-reference and hierarchically organize notes
LCS is an evidence-based medicine library consult service web application designed to facilitate physicians' use of the research literature. Physicians submit clinical questions to the system, librarians respond, and physicians rate the responses.
Cloud data warehouse to power your data-driven innovation
BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
This is a way of creating virtual libraries. I catalogue the books (or DVDs etc.) that I have. My friends do the same. As well as allowing me to organise myself easily is also means that if I'm after a book I can easily find which of my friends has it.