List of Graphwise Customers
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Since 2010, our global team of researchers has been studying Graphwise customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Graphwise for Natural Language Processing from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Graphwise for Natural Language Processing include: British Broadcasting Corporation, a United Kingdom based Media organisation with 21273 employees and revenues of $7.18 billion, Financial Times, a United Kingdom based Media organisation with 2300 employees and revenues of $480.0 million and many others.
Contact us if you need a completed and verified list of companies using Graphwise, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Graphwise customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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British Broadcasting Corporation | Media | 21273 | $7.2B | United Kingdom | Graphwise | Graphwise | Natural Language Processing | 2010 | n/a |
In 2010, the British Broadcasting Corporation implemented Graphwise as a Natural Language Processing solution to power the BBC FIFA World Cup web site. The project applied semantic publishing technology from Ontotext, now part of Graphwise, to automate editorial publishing flows and improve site navigation for match coverage.
The deployment centralized semantic text analysis and knowledge graph capabilities to automate content creation, enable dynamic aggregations, and improve reuse of editorial assets. Graphwise was configured to tag and semantically enrich articles and to generate dynamic aggregations for editorial pages, with over 800 dynamic aggregations reported during the event.
Operational scope focused on the media and publishing site for the 2010 FIFA World Cup in the United Kingdom, impacting editorial and publishing functions across BBC sports production teams. Integrations were oriented toward feeding semantically enriched content into site rendering and editorial workflows, and Graph NLP and text analysis usage is inferred from the case study.
Governance and workflow restructuring embedded semantic enrichment into content authoring and aggregation pipelines to support automated page composition and asset reuse. The project explicitly reported improved discoverability and efficiency and cited reduced editorial cost through semantic publishing and automated aggregations.
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Financial Times | Media | 2300 | $480M | United Kingdom | Graphwise | Graphwise | Natural Language Processing | 2014 | n/a |
In 2014, Financial Times implemented Graphwise as a Natural Language Processing platform. Ontotext worked with Financial Times to rebuild a semantic backend in the United Kingdom, concentrating the engagement on media and publishing use cases around semantic search and recommendation capabilities.
The implementation of Graphwise delivered core Natural Language Processing functions including semantic search, content recommendation and personalization features, ontology and taxonomy management, and entity extraction pipelines. Graphwise was configured to power semantic indexing and to expose recommendation endpoints that support editorial discovery and reader personalization, aligning with typical NLP semantic graph architectures.
Deployment integrated the Graphwise semantic backend with Financial Times content stores and publishing workflows to surface recommendations within reader-facing channels and editorial tools. Operational coverage included editorial and product teams within the UK publishing operation, with the Graphwise Natural Language Processing platform serving as the semantic layer for content metadata and recommendation delivery.
Governance work included establishing taxonomy ownership and recommendation rule workflows to guide editorial oversight and algorithmic curation. The engagement explicitly produced content recommendations to improve discoverability and personalization, implemented through the Graphwise Natural Language Processing deployment.
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