List of Datapolis Process Intelligence Customers
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Since 2010, our global team of researchers has been studying Datapolis Process Intelligence 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 Datapolis Process Intelligence for Process Mining 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 Datapolis Process Intelligence for Process Mining include: Microsoft, a United States based Professional Services organisation with 221000 employees and revenues of $243.00 billion, United States Army, a United States based Government organisation with 453551 employees and revenues of $65.25 billion, Burger King, a United States based Retail organisation with 34800 employees and revenues of $27.02 billion, ING, a Netherlands based Banking and Financial Services organisation with 60000 employees and revenues of $24.78 billion, Johnson Controls, a Ireland based Professional Services organisation with 94000 employees and revenues of $22.95 billion and many others.
Contact us if you need a completed and verified list of companies using Datapolis Process Intelligence, 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 Datapolis Process Intelligence 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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AngloGold Ashanti | Oil, Gas and Chemicals | 70000 | $1.0B | South Africa | Datapolis | Datapolis Process Intelligence | Process Mining | 2010 | n/a |
In 2010, AngloGold Ashanti implemented Datapolis Process Intelligence to establish Process Mining capability across its global operations. The deployment of Datapolis Process Intelligence was positioned to enable process discovery and operational analytics, linking event-level data to business process models to support process discovery, conformance checking and performance analysis for core business functions.
The implementation emphasized Datapolis Process Intelligence modules for process visualization, variant analysis, case-level drilldown and automated KPI extraction, with configuration focused on mapping event logs and transactional records into a unified process data model. Data ingestion and preprocessing workflows were configured to normalize timestamps, case identifiers and activity semantics to enable cross-site comparability within the Process Mining platform.
Operational coverage extended across EMEA, Arabic Gulf, South Africa and Latin America, targeting finance, procurement and frontline operations as primary business functions. Architecture was described as a centralized analytics instance feeding site level data collectors and dashboards to local process owners, enabling centralized model governance while preserving regional operational context.
Governance and rollout combined centralized process governance with partner channel enablement, the latter including partner capacity building, license and sales systems through the partner network and negotiated end user contracts with strategic customers. Training, stakeholder alignment across business units and phased regional rollouts were used to operationalize Datapolis Process Intelligence and embed Process Mining into ongoing process improvement workflows.
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Burger King | Retail | 34800 | $27.0B | United States | Datapolis | Datapolis Process Intelligence | Process Mining | 2010 | n/a |
In 2010, Burger King implemented Datapolis Process Intelligence, deploying a Process Mining application to increase visibility into restaurant operations and back office workflows. The Burger King Datapolis Process Intelligence Process Mining initiative targeted process discovery and monitoring across operational touchpoints and shared service functions, establishing a foundation for process model extraction and event log analysis.
Datapolis Process Intelligence was configured to deliver process discovery, conformance checking, variant analysis, performance monitoring, and KPI visualization, aligning analytical modules with operational and back-office process improvement workflows. The implementation emphasized interactive process visualizations, process variant dashboards, and root cause drill downs to support continuous process investigation and standardization.
Rollout and commercial governance used a partnership-driven channel model, with capacity building, partner agreements, and end user contract negotiation supporting deployments across EMEA, the Arabic Gulf, South Africa and Latin America. Operational ownership and vendor cooperation were structured around partner-enabled sales and service delivery, with direct cooperation involving strategic enterprise customers during contract and deployment phases.
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GridPoint | Professional Services | 180 | $25M | United States | Datapolis | Datapolis Process Intelligence | Process Mining | 2012 | n/a |
In 2012, GridPoint implemented Datapolis Process Intelligence. Datapolis Process Intelligence is a Process Mining application deployed to analyze SharePoint based workflows and human centric processes used across GridPoint's professional services and operations.
The implementation leveraged Datapolis's SharePoint native approach and the Datapolis Workbox architecture, using a graphical designer to model process layers and technical automation logic. Core capabilities implemented included event log ingestion from SharePoint lists and workflow tasks, process discovery and visualization, variant analysis and conformance checking, and dashboarding for process owners. The configuration emphasized mapping business phases to technical workflow rules, enabling readable, changeable workflow models and supporting manual task orchestration where automation was not applied.
Integration centered on SharePoint as the operational data source, with Datapolis Process Intelligence consuming workflow events from Datapolis Workbox deployments and SharePoint content stores. Operational coverage targeted IT, process owners and operations teams who manage and monitor SharePoint based processes. Governance was structured around the dual business and technical layer model, enabling formalized process documentation, change control of workflow logic, and ongoing monitoring of process variants for remediation or further automation.
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Banking and Financial Services | 60000 | $24.8B | Netherlands | Datapolis | Datapolis Process Intelligence | Process Mining | 2011 | n/a |
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Professional Services | 94000 | $23.0B | Ireland | Datapolis | Datapolis Process Intelligence | Process Mining | 2010 | n/a |
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Aerospace and Defense | 3500 | $1.2B | United States | Datapolis | Datapolis Process Intelligence | Process Mining | 2012 | n/a |
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Professional Services | 221000 | $243.0B | United States | Datapolis | Datapolis Process Intelligence | Process Mining | 2012 | n/a |
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Manufacturing | 21108 | $8.4B | France | Datapolis | Datapolis Process Intelligence | Process Mining | 2010 | n/a |
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Banking and Financial Services | 30157 | $14.1B | Finland | Datapolis | Datapolis Process Intelligence | Process Mining | 2012 | n/a |
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Manufacturing | 1100 | $200M | United States | Datapolis | Datapolis Process Intelligence | Process Mining | 2012 | n/a |
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Buyer Intent: Companies Evaluating Datapolis Process Intelligence
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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