Shruta (Company Brain) — Enterprise Vector Knowledge Engine & Secure SOP Retriever: "A secure internal search engine that indexes scattered Slack, Notion, and PDF SOPs for AI tools."
Corporate Knowledge Fragmented Across Dozens of Tools
Critical company knowledge lives buried in scattered Slack threads, old Notion pages, and PDF SOPs. When employees or internal AI tools search for answers, standard search returns out-of-date or out-of-context snippets leading to costly errors.
Hierarchical Document Chunking & Department Access Tags
We engineered a knowledge pipeline combining parent-child document chunking, keyword hybrid search, and strict database row-level permissions.
Hierarchical Chunking
Preserved document titles and table structures so retrieved snippets retain their full context.
Hybrid Keyword & Vector Search
Combined semantic vector search with exact keyword matching to handle technical part numbers and internal acronyms.
Department Permission Tags
Enforced strict role-based access control directly in the vector database query level.
Unified Neural Search Engine for Enterprise Operational Knowledge
Transforms unstructured corporate docs into grounded context for teams and AI agents.
Multi-Source Knowledge Connectors
Syncs automatically with Slack conversations, Notion workspaces, and PDF SOP drives.
Hybrid Search & Reranking Console
Delivers grounded answers with exact source document breadcrumbs and confidence scores.
Executable AI Tool Stubs
Converts retrieved knowledge directly into executable tool definitions for AI agents.
65% Reduction in Internal Query Time & 98.2% Precision
Shruta turned disorganized corporate knowledge into a secure, grounded neural brain for internal team productivity.
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