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Discover the AI Assistant for literature search and summaries that helps researchers and students find citations, streamline reviews, and track topics for free.
Semantic Scholar is a free, open-access academic search engine.
Monitor AI for Coding experiments and training runs with an experiment-tracking platform that centralizes model metrics, logs, and reproducible workflows.
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Build and deploy LLM models and datasets on a collaborative platform for researchers and teams, with tools for training and production integration.
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Index vectors for LLM retrieval, enabling fast semantic search, scalable embedding storage, and easier integration into Data Science and analytics workflows.
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Organize Education literature, discover related studies, and build saved libraries with visual maps to speed literature reviews and improve academic writing.
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Explore Education literature maps to visualize scholarly networks, find influential papers, and build bibliographies for research and Data Science.
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Train LLMs, fine-tune, and deploy models privately or in cloud with configurable agents, orchestration, and developer tools for enterprise data control.
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Explore Data Analytics insights from scientific literature to summarize evidence, extract key findings, and speed informed decisions for researchers, teams.
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Summarize research with an LLM to create concise citation-backed summaries, extract references, and generate structured notes for academic literature review.
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Build scalable vector search for LLMs with real-time indexing, hybrid dense-sparse retrieval, multivector support, and metadata filters for Data Analytics.
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Accelerate research with an AI Assistant that finds, summarizes, and organizes research to support reproducible workflows for data science teams.
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