HR_Builds

MindMesh is a multimodal AI-powered knowledge workspace that transforms fragmented information from multiple data sources into connected, searchable, and actionable knowledge. It enables users to upload and interact with diverse content formats, including PDFs, images, spreadsheets, code files, text documents, and meeting transcripts. Using multimodal AI models, it understands the content, extracts meaningful information, identifies entities and relationships, and organizes the knowledge into a unified knowledge layer. The system combines hybrid retrieval (Vector Search + BM25), reranking, and Knowledge Graph-based traversal to retrieve relevant information across multiple documents. An AI reasoning layer then uses the retrieved evidence to generate context-aware answers with source citations, while a verification mechanism helps ensure that responses are supported by the underlying documents. When sufficient evidence is unavailable, the system can abstain rather than generate unsupported answers. Core objectives 1. Multimodal Ingestion: Process information from different file formats and data sources. 2. Intelligent Understanding: Extract text, visual information, entities, concepts, and relationships using AI models. 3. Connected Knowledge: Build relationships between information scattered across multiple documents using Knowledge Graphs. 4. Advanced Retrieval: Combine semantic search and keyword search with reranking and graph traversal. 5. Evidence-Based Reasoning: Generate grounded answers with verifiable source citations. 6. Visual Intelligence: Generate diagrams, illustrations, and visual explanations from retrieved knowledge. 7. Reliable Responses: Validate citations and support abstention when relevant evidence is unavailable.