Knowledge mining in contract management

Cognitive Search
Form Recognizer
Text Analytics

Solution ideas

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This architecture demonstrates how to use knowledge mining in contract management.

Potential use cases

Many companies create products for multiple sectors. Because these companies work with various vendors and buyers, their business opportunities increase exponentially. Knowledge mining can help organizations scour thousands of pages of sources to create a competitive bid. Minor details in the bidding process can make the difference between a healthy profit or lost opportunity on a project.

Industries that rely on knowledge mining for contract management include:

  • Marketing.
  • Retail.
  • Logistics.
  • Manufacturing.

Architecture

There are three steps in knowledge mining: ingest, enrich, and explore.

Architecture Diagram: knowledge mining in contract management, with three steps: ingest, enrich, and explore.

Download a Visio file of this architecture.

Dataflow

  • Ingest

    The ingest step aggregates content from a range of sources, including structured and unstructured data. For contract management, you can ingest different types of content like user guides, forms, product manuals, product pricing proposals, cost sheets, and project reports.

  • Enrich

    The enrich step uses AI capabilities to extract information, find patterns, and deepen understanding. The content is enriched by using key phrase extraction, optical character recognition, entity recognition, and customized models to flag potential risk or essential information.

  • Explore

    The explore step is exploring data via search, bots, existing business applications, and data visualizations. For example, you can integrate the search index into a portal to expand the knowledge base as users share more information.

Components

The following key technologies are used to implement tools for technical content review and research:

  • Azure Cognitive Search is a cloud search service that supplies infrastructure, APIs, and tools for searching. You can use Azure Cognitive Search to build search experiences over private, heterogeneous content in web, mobile, and enterprise applications.
  • The web API custom skill interface is used to integrate a custom skill into an Azure Cognitive Search enrichment pipeline.
  • Azure Cognitive Service for Language is part of Azure Cognitive Services that offers many natural language processing services. You can use these services to understand and analyze text.
  • Text analytics is a collection of APIs and other features from Azure Cognitive Service for Language that you can use to extract, classify, and understand text within documents.
  • Azure Cognitive Services Translator is part of the Cognitive Services family of REST APIs. You can use Translator for real-time document and text translation.
  • Azure Form Recognizer is part of Azure Applied AI Services. Form Recognizer uses machine-learning models to extract key-value pairs, text, and tables from documents such as invoices, receipts, ID cards, and business cards.

Next steps