BrahmaSumm is an enterprise knowledge discovery platform that helps organizations unlock insights hidden across 150,000+ documents through AI-powered search, visualization, and knowledge graphs. The platform combines vector and graph RAG technologies to enable semantic search, automatic summarization, and interactive data exploration across formats like PDFs, spreadsheets, and presentations. It supports air-gapped deployment for security-conscious enterprises and integrates with existing workflows on Teams, email, and docs.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises accumulate vast repositories of documents—often exceeding 150,000 files—where critical insights remain buried and inaccessible. Traditional keyword-based search tools fail to surface contextually relevant information, forcing teams to spend excessive time manually sifting through files and missing connections between related data points.
Solution
BrahmaSumm provides an enterprise knowledge discovery platform that transforms unstructured documents into searchable, visual, and actionable insights. The platform uses a combination of vector and graph RAG (retrieval-augmented generation) to enable deep semantic search across formats like PDFs, spreadsheets, and presentations, returning contextually relevant answers with summaries and data visualizations. Users can build interactive knowledge graphs from internal data and chat with them to surface answers to pressing business questions. The system also automates document summarization, table extraction, version-difference analysis, and even code generation from technical spec sheets. With support for air-gapped deployment and integration with existing tools like Teams and email, BrahmaSumm ensures data privacy while making institutional knowledge accessible and actionable.
Target Audience
Primary customers are mid-to-large enterprises across knowledge-intensive industries such as legal, finance, engineering, and research that need to extract value from large volumes of internal documents while maintaining strict data security and privacy controls.
Features
- Deep vector and graph search combining semantic retrieval with relationship mapping for context-aware document discovery
- Interactive knowledge graphs that users can query conversationally to surface insights across connected data points
- Advanced table extraction that converts complex tables from PDFs and spreadsheets into structured, analyzable data
- Automatic data visualizations that transform raw numeric data into charts and graphs for faster trend analysis
- Custom document summarization with adjustable length, format, and content focus to match user needs
- Version management and summarization that highlights changes between document revisions for efficient review
- Code generation from technical specification sheets, producing snippets, scripts, or templates automatically
- Air-gapped deployment option for organizations requiring complete data isolation and security