Doc2Graph™

Take control over unstructured data collections with industry leading AI and NLP tech. Lymba’s Doc2Graph™ populates a Knowledge Graph from input documents according to a provided or automatically generated schema/ontology. Doc2Graph™ recognizes target concepts and the relations between concepts in free-flowing text, tables, hierarchical document structures and supports a variety of graph vendors as plug-and-play. 

Use Cases

• Understanding lease agreement at scale: accurately and automatically extract contract clauses from lease agreements, and store in a RDBMS database for querying and report generation. Lymba’s pipeline captures the exact meaning of contract provisions and extracts contract paragraphs that match that meaning. 

• Extracting key financial metrics and forecasting from financial research documents: specific ontologies are used to process research reports, convert documents via Doc2Graph™, store the output in a Knowledge Graph, and use NL2Query™ to retrieve data. 

• Classifying goods according to custom tax tariff: machine learning techniques, and custom domain ontologies created to cover commonsense product information has allowed faster review, better accuracy and lower costs. 

• Extracting parameters & features from complex product documentation: Lymba’s semantic Document Comparison NLP solution transforms complex product data sheets into actionable knowledge. 

• Compiling client information to automatically support insurance underwriting: Lymba can provide an automated and intelligent way to semantically understand key data and relationships, enabling true semantic document comparison, disambiguating terms with multiple meanings, and transforming data sources into unified and searchable asset. 

  Outcome: Lymba has helped save thousands of man-hours and reduced costs due to its accuracy in automatically extracting key information, populating knowledge graphs with unstructured text, generating summaries and reports.