xMentium Document Intelligence Platform

An AI-powered SaaS platform to unlock trapped data and gain insights from unstructured documents

Enterprises need AI that delivers precise document data extraction and analysis while maintaining business context. LLMs and VLMs alone lack accuracy for documentation language, images, data extraction and your business context. xMentium fixes that by rapidly classifying, tagging, analyzing, and relating millions of complex unstructured documents for efficient operations, improved workflows, and optimized financial performance.

Speed Your Business

• Superior Data Extraction: Extract precise information from complex business documents including P&IDs, inspection isometrics, quality reports, 3D scans, SOPs, diagrams, images, handwritten text, and contracts
• Cross-Functional Business Intelligence: Empower legal, operations, finance, and compliance teams with unified views of contractual obligations, regulatory requirements, and commitments
• Strategic Portfolio Analysis: Transform document data into comprehensive enterprise intelligence, expense and efficiency analysis
• Process Optimization: Streamline workflows by automatically surfacing relevant information, reducing manual review time, and eliminating data blind spots

Transform unstructured document data into tagged and searchable data assets to reveal previously unavailable insights:

• Import: Ingest documents from any source. Connect to repositories and business systems
• Enrich: Automatically tag clauses, images, terms, and entities. Transform into structured, searchable data
• Analyze: Uncover patterns, risks, and opportunities across millions of documents with Knowledge Set Insights
• Distribute: Push actionable data and report insights using APIs, and integrations so intelligence powers business decisions

Professional Services

Implementation supported by experts in AI, language and system integration:

1. Analyze: Review classification metadata for document classes, functional tags, equipment IDs and other logical identifiers. Gather documents and perform batch analysis. Target network drives, SharePoint servers, Asset Catalogs and business systems.
2. Configure (100s of documents): Configure AI tagging models. Import and refine classification metadata. Configure import routing batching pipelines. Create automations. Integrate document systems. Assess baseline. Engage stakeholders.
3. Tune (1,000s of documents): Optimize extraction automations for quality and cost. Implement multi-language capability. Monitor tagging quality. Tune xMentium including classification refinement and AI automations, to maximize accuracy.
4. Rollout (Millions of documents): Release production pipeline automations. Optimize model quality monitoring and cost. Connect more network drives. Drive knowledge sharing, training, user support and enterprise change management.

Real-world Use Cases

Document Intelligence drives $10-100M annual savings and process improvements:

• Operational Optimization: Analyze supplier contracts, engineering documents, SOPs, quality records, and service agreements to identify maintenance optimization opportunities, process inefficiencies, unexploited revenue streams, and free resources to innovate.
• Revenue Leakage Identification: Detect missed billing opportunities, contract deviations, and pricing inconsistencies across customer and supplier agreements to enable lost revenue recovery, optimize costs, and prevent future leakage.
• Asset Intelligence: Extract critical information from engineering documents, SOPs, service agreements, and supply contracts to create Asset Registries linking component IDs and other logical identifiers with associated documents for enhanced asset management and analysis.

Enterprise Scale

• Enterprise AI Models: Powered by Azure and Azure AI, xMentium models are trained to understand your documents. No tuning required.
• Automated Tagging: Automatically classify and capture IDs, terms, obligations, dates, and critical information based on your enterprise taxonomy and business requirements.
• Automated Ingestion, Extraction, and Tagging: OCR, LLM, VLM, NER, Regex, LLM cost and quality management, chunking, grouping, and multi-dimensional tagging and analysis orchestrated at scale.
• Review Console: A side-by-side UI for human-in-the-loop tag quality review and data enhancement.
• Enterprise Data Integration: Export contextually tagged document data into your Asset Repository and systems, enabling teams to search across the document database by user-specified logical identifiers.
• Governance & Security: SOC 2 compliant.