Vectorize @Vectorizeio

Vectorize makes it easy to turn your unstructured data into always-up-to-date vector data to power your generative AI applications. platform.vectorize.io Boulder, CO Joined December 2023

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Vectorize @Vectorizeio

7 hours ago

15 Easy Chunking Strategies (with Examples!)! Retrieval-Augmented Generation (RAG) depends heavily on how we chunk our data. If you want the LLM to retrieve context that actually makes sense, you must chunk your data thoughtfully. Here are 15 key chunking strategies, explained…

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Vectorize @Vectorizeio

2 days ago

Chat Widget — one code snippet, infinite conversations. Embed an assistant on your site, docs, or app in minutes. No glue code. No duplicate knowledge base. Why it matters: Uses the same RAG pipelines you already run Lighter than an SDK, smarter than an iframe Configure…

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Vectorize @Vectorizeio

3 days ago

Supercharge Your RAG Pipelines with Structured Information! Automatic Metadata Extraction is now available in Vectorize! This powerful addition transforms how you work with documents in your RAG pipelines. This feature allows you to extract structured information from your…

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Vectorize @Vectorizeio

3 days ago

Turn Unstructured Data Into AI-Ready Knowledge! RAG Pipelines transform your documents, PDFs, and knowledge bases into searchable vector embeddings. Connect any data source, process at scale, and deliver accurate AI responses in minutes, not months. Start building AI…

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Vectorize @Vectorizeio

4 days ago

5 Reasons this RAG AI Chat Agent is a GAMECHANGER! Discover the revolutionary new RAG AI chat agent that is transforming the way we interact with conversational ai systems. This game-changing technology offers unparalleled AI accuracy. With its advanced capabilities, the RAG…

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Vectorize @Vectorizeio

5 days ago

AGUI(Agent to UI Protocol): What Should Backend and Frontend Developers Know! AG-UI is another piece that completes the puzzle of the development of AI Tools. Let’s see what it is, and what we should do as web developers and software engineers. Know more about AGUI(Agent to UI…

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Vectorize @Vectorizeio

5 days ago

Optimize Your RAG Performance Before Deployment! RAG Evaluation tests multiple retrieval strategies in parallel, helping you find the perfect configuration for your data. Prevent hallucinations, maximize accuracy, and ensure your AI delivers reliable results from day one. Start…

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Vectorize @Vectorizeio

a week ago

MCP-Powered Agentic RAG Architecture Overview! The diagram below illustrates the complete workflow, from the user’s initial question to the final, context-enriched answer. The architecture is composed of several key components that work in concert: The User: The starting…

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Vectorize @Vectorizeio

a week ago

Practical Tips for Context Engineering: - Use RAG for Retrieval: Integrate vector databases like Pinecone or Weaviate for efficient semantic memory retrieval. - Summarize Long Histories: Compress conversation histories to avoid token limits. LangGraph’s utilities can summarize…