Supametas.AI
Supametas.AI is a platform that transforms unstructured data into structured formats suitable for use in large language models (LLMs) and retrieval-augmented generation (RAG) systems. The platform is designed to simplify data collection, construction, and preprocessing for industry-specific datasets, making it easier for companies to bypass complex data cleaning processes. Users can convert data from multiple sources such as APIs, URLs, local files, images, audio, and video into JSON and Markdown formats, which are then seamlessly integrated into LLM RAG knowledge bases.
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Graviti
Unstructured data is the future of AI. Unlock this future now and build an ML/AI pipeline that scales all of your unstructured data in one place. Use better data to deliver better models, only with Graviti. Get to know the data platform that enables AI developers with management, query, and version control features that are designed for unstructured data. Quality data is no longer a pricey dream. Manage your metadata, annotation, and predictions in one place. Customize filters and visualize filtering results to get you straight to the data that best match your needs. Utilize a Git-like structure to manage data versions and collaborate with your teammates. Role-based access control and visualization of version differences allows your team to work together safely and flexibly. Automate your data pipeline with Graviti’s built-in marketplace and workflow builder. Level-up to fast model iterations with no more grinding.
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Tensorlake
Tensorlake is the AI data cloud that reliably transforms data from unstructured sources into ingestion-ready formats for AI applications. It seamlessly converts documents, images, and slides into structured JSON or markdown chunks, ready for retrieval and analysis by LLMs. The document ingestion APIs parse any file type, from hand-written notes to PDFs to complex spreadsheets, performing post-processing steps like chunking and preserving the reading order and layout of the documents. Tensorlake's serverless workflows enable lightning-fast, end-to-end data processing, allowing users to build and deploy fully managed Workflow APIs in Python that scale down to zero when idle and scale up when processing data. It supports processing millions of documents at once, maintaining context and relationships between various data formats, and offers secure, role-based access control for effective team collaboration.
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Qwen2.5-VL
Qwen2.5-VL is the latest vision-language model from the Qwen series, representing a significant advancement over its predecessor, Qwen2-VL. This model excels in visual understanding, capable of recognizing a wide array of objects, including text, charts, icons, graphics, and layouts within images. It functions as a visual agent, capable of reasoning and dynamically directing tools, enabling applications such as computer and phone usage. Qwen2.5-VL can comprehend videos exceeding one hour in length and can pinpoint relevant segments within them. Additionally, it accurately localizes objects in images by generating bounding boxes or points and provides stable JSON outputs for coordinates and attributes. The model also supports structured outputs for data like scanned invoices, forms, and tables, benefiting sectors such as finance and commerce. Available in base and instruct versions across 3B, 7B, and 72B sizes, Qwen2.5-VL is accessible through platforms like Hugging Face and ModelScope.
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