Polyvia AI is a visual knowledge indexing platform designed to transform unstructured visual data—such as charts, tables, slides, and diagrams—into a structured, queryable knowledge graph. This enables developers and knowledge-work teams to access and reason over visual information at scale, facilitating accurate and audit-ready insights. Key Features: - Visual Logic Extraction (VLM-OCR): Utilizes advanced Visual Language Models to extract underlying visual logic from complex infographics, converting them into structured, machine-readable data points. - Connected Knowledge Graph: Disambiguates and tags facts with contextual information (e.g., company, quarter, source document) to create a unified knowledge graph, ensuring a single source of truth for high-confidence retrieval and analysis. - Cross-Document Agentic Reasoning: Enables agents to query and connect facts across tens of thousands of documents simultaneously, supporting complex analytical questions that require synthesizing information from multiple sources. - Audit-Ready Visual Citations: Provides full traceability by grounding every answer in the source material, with visual citations linking directly to the original document, page, section, and specific visual element. Primary Value: Polyvia AI addresses the challenge of accessing and reasoning over unstructured visual data by transforming scattered visual elements into a cohesive, queryable knowledge graph. This empowers multimodal agents and internal teams to perform accurate, verifiable, and sophisticated visual reasoning at an enterprise scale, enhancing data analysis and decision-making processes.