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Knowledge mining

Uncover latent insights from all your content

What is knowledge mining?

Knowledge mining is an emerging discipline in artificial intelligence (AI) that uses a combination of intelligent services to quickly learn from vast amounts of information. It allows organisations to deeply understand and easily explore information, uncover hidden insights, and find relationships and patterns at scale.

Ingest your content from Azure sources like Azure Blob storage, Azure Table storage, Azure SQL Database, and Azure Cosmos DB, as well as hundreds of third-party sources, via dedicated connectors.

Extract text-based content from file formats such as PDF, Microsoft Word, PowerPoint, and CSV. See the full list of supported formats.

Work across different document types and formats, including images, audio files, forms, web pages, and Office documents, without the cost and complexity of building and managing individual AI services.

Enrich your understanding of the content with cognitive skills, such as image classification, face recognition, language detection, and key phrase extraction. These operations let you produce new fields in your search index that are not available natively in the source.

Integrate custom models or classifiers that can be built with any language or framework of your choice. Explore insights with pre-configured search, or through analytics tools and business applications.

Supplement with custom analysers, invoke fuzzy search queries, add contextual search or set weighted parameters for your unique scenario.

How knowledge mining works

By orchestrating various AI capabilities, knowledge mining delivers an enhanced experience that enables organisations to gain insights faster from content that would otherwise remain untapped. There are three phases to knowledge mining: ingest, enrich and explore.


Ingest content from a range of sources, using connectors to first and third-party data stores.


Enrich the content with AI capabilities that let you extract information, find patterns, and deepen understanding.


Explore the newly indexed data via search, bots, existing business applications and data visualisations.

Learn more about knowledge mining products and services

Learn more through example solution architectures

Content research

When organisations task employees to review and research technical data, it can be tedious to read page after page of dense text. Knowledge mining helps employees quickly review these dense materials.

Auditing, risk, and compliance management

Developers could use knowledge mining to help attorneys quickly identify entities of importance from discovery documents and flag important ideas across documents.

Business process management

In industries where bidding competition is fierce, or when the diagnosis of a problem must be quick or in near real-time, companies can use knowledge mining to avoid costly mistakes.

Customer support and feedback analysis

For many companies, customer support is costly and inefficient. Knowledge mining can help customer support teams find the right answer quickly for a customer enquiry or assess customer sentiment at scale.

Digital asset management

Given the amount of unstructured data created daily, many companies are struggling to make use of or find information within their files. Knowledge mining through a search index makes it easy for end customers and employees to locate what they are looking for faster.

Contract management

Many companies create products for multiple sectors, hence the business opportunities with different vendors and buyers increases exponentially. Knowledge mining can help organisations to scour thousands of pages of sources to create an accurate bid.

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Customers are doing great things with knowledge mining

Learn how the Dutch shipbuilding pioneer uses knowledge mining to search more than a million documents in under two seconds, speeding time to resolution and improving customers’ experience.

Royal IHC

This global engineering company uses knowledge mining to create more accurate bid proposals and reclaim the time it would take to manually compile them.


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