Turn your documents into an intelligent knowledge base your AI can search, understand, and reason over.
OpenRails transforms your documents into a searchable knowledge layer in four steps:
Add documents through the dashboard, API, web crawler, or connectors. OpenRails handles PDFs, Office documents, images, video, audio, and more.
Documents are automatically parsed, split into meaningful segments, and indexed. Images are OCR'd, audio and video are transcribed. The system extracts both content and relationships between concepts.
When users ask questions, OpenRails searches your knowledge base using two complementary approaches — finding content that matches the meaning of the question AND tracing relationships between concepts for deeper understanding.
Search results are filtered by the user's access level, then passed to the AI model to generate an accurate, sourced answer. Citations link back to the original documents.
Most AI platforms rely on a single search method. OpenRails combines two approaches for significantly better results:
Finds content that matches the meaning of a question, even when the exact words don't appear. Great for natural language queries across large document sets.
Traces relationships between people, places, concepts, and events. Answers "who reported to whom" or "which products are affected by this regulation" by understanding connections.
Data lakes let you organize your knowledge into logical collections — by department, project, topic, or any structure that fits your organization:
Security is enforced at every level of the knowledge pipeline. Documents and collections are assigned security tiers, and access controls follow the content all the way through to AI-generated responses.
OpenRails handles all major document formats out of the box: