Graphlit

Ragie streamlines data ingestion, chunking, and multimodal indexing of structured and unstructured data. Connect directly to your own data sources, ensuring your data pipeline is always up-to-date. Built-in advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search help you deliver state-of-the-art generative AI. Connect directly to popular data sources like Google Drive, Notion, Confluence, and more. Automatic syncing keeps your data up-to-date, ensuring your application delivers accurate and reliable information. With Ragie connectors, getting your data into your AI application has never been simpler. With just a few clicks, you can access your data where it already lives. Automatic syncing keeps your data up-to-date ensuring your application delivers accurate and reliable information. The first step in a RAG pipeline is to ingest the relevant data. Use Ragie’s simple APIs to upload files directly.

Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback. Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases. The best models are built on user data. Programmatically gather unusual or underperforming examples to retrain your model. Stop manually reviewing thousands of outputs when changing your prompt or model. Evaluate your LLM-powered apps programmatically. Detect and fix degradations quickly. Monitor new deployments in real-time and seamlessly edit the version of your app your users interact with. Connect your self-hosted or third-party model and your existing data sources. Process enterprise-scale data with our serverless streaming dataflow engine. Gantry is SOC-2 compliant and built with enterprise-grade authentication.