Unsiloed

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.

Product information: Parsebridge is a PDF parsing API that transforms PDFs into clean, structured Markdown. It extracts text, tables, and data from PDF documents with a powerful API built for developers who need reliable document parsing at scale. Complex PDFs, tables, multi-column layouts, nested structures, and scanned pages are handled in one API call, turning the hard parts that usually break other parsers into Markdown you can actually use. Merged cells, nested headers, and complex layouts are parsed correctly instead of coming back garbled. Parsebridge supports live testing by pasting a PDF URL or uploading a PDF to the preview page-one Markdown without an account. It currently supports PDF files only, focusing on extraction quality for PDF documents, with files up to 100MB supported. Under the hood, Parsebridge uses Docling, an open source parser known for table extraction and layout preservation, while the platform handles infrastructure, OCR, scaling, and the API layer on top.