Document Intelligence: Generative AI That Transforms Your Processes
Document Intelligence is Datlas' platform that transforms complex, unstructured content into structured, actionable data, enabling more efficient processes and faster decision-making.
What Is Document Intelligence
Document Intelligence is a proprietary platform that uses generative AI and LLMs to automate document-based processes and enable advanced Knowledge Base management.
It goes beyond simple data extraction:
- interprets content,
- applies domain-specific logic,
- checks consistency across documents and supports both fully automated and human-in-the-loop operating models.
How Our AI Platform Works
Our generative AI solution follows a structured six-stage process:
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Data Ingestion & Normalization
Ingestion and normalization of structured and unstructured data from CRMs, email, ERPs, forms and portals.
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Reading & Detection
Recognition of text, tables, signatures, checkboxes and layouts using Computer Vision, Machine Learning and generative AI.
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Understanding
Semantic understanding of document content and automatic classification based on domain-specific logic.
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Extraction & Validation
Automatic data extraction and validation against agreed business rules.
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Distribution
Integration via APIs, dashboards, ERP/CRM systems or automated notifications.
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Insight Generation
Generation of strategic insights through semantic analysis, clustering and predictive models.
Document Intelligence Use Cases
Document Intelligence can be applied across a wide range of use cases.
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Customer & Partner Onboarding
Classifies identity documents, certifications, contracts and administrative forms, checking that all required information is complete.
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Contract Management & Compliance
Identifies clauses, dates, signatures, versions and contract metadata, supporting audits and regulatory compliance.
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Customer Care
Analyzes emails and attachments, interprets customer intent, recommends procedures and generates contextualized draft responses.
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Claims Management
Analyzes insurance documents, medical reports, official records and communications, checking consistency across the information provided.
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Finance & Back Office
Extracts data from invoices, receipts, expense reports and accounting documents, integrating the information with ERP systems and financial control platforms.
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Knowledge Management
Organizes complex documentation, removes duplicates and makes information easy to query for both operators and intelligent systems.
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Document Analysis
Uses advanced semantic analysis to identify patterns, recurring issues and opportunities to optimize business processes.
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End-to-End Automation
Automates the segmentation, classification, extraction, validation and distribution of information to enterprise systems, reducing processing costs.
Proprietary AI Technologies
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Text Extraction with Layout Preservation
An advanced OCR and spatial analysis system preserves the document's original structure, recognizing tables, alignments, fields and relationships between labels and values.
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Multimodal Classification
A classification engine that combines text, structure and context to accurately identify document type and content, even in complex scenarios.
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Schema-Guided Structured Extraction
A question-driven, schema-driven approach that delivers precise and consistent data, rather than simple summaries, even from complex documents.
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Intelligent Model Routing
Dynamic selection of the most suitable model based on document type, required accuracy, privacy constraints and cost optimization.
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Multi-Level Hierarchical Analysis
The ability to process complex document collections through successive levels of analysis, synthesis and aggregation, while preserving context across individual elements.
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Advanced Aggregation & Summarization
Aggregation techniques that improve the robustness and quality of results across large document volumes.
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Semantic Tagging & Clustering
Automatically classifies and groups documents by category and content, enabling cross-document analysis and easier knowledge navigation.