AI Buyer Insights:

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Michelin, an e2open customer evaluated Oracle Transportation Management

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Michelin, an e2open customer evaluated Oracle Transportation Management

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

List of KNIME Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Deutsche Telekom Communications 201336 $134.1B Germany KNIME KNIME ML and Data Science Platforms 2021 n/a
In 2021, Deutsche Telekom implemented KNIME Analytics Platform to automate month end closing procedures and deviations analysis within its B2C controlling function, using the application as part of its ML and Data Science Platforms tooling. The engagement focused on embedding KNIME Analytics Platform into recurring financial close workflows, with the platform operating as the analytic and orchestration layer for deviation detection and narrative generation. The implementation delivered functional capabilities for automated deviations analysis, rule driven comment generation, and generation of deviation reports sourced from SAP BW. A small digitalization team designed and configured data workflows, transformation logic, and automation pipelines in KNIME Analytics Platform, producing a production ready solution within three months. Integration points were explicit and narrow, KNIME consumed reporting-level data from SAP BW and the solution was coupled with a Blue Prism bot that transferred the auto generated comments into downstream FP&A consumption channels. Operational scope centered on B2C controlling and FP&A activities in Germany, connecting analytic outputs to robotic process automation for handoff and distribution. Governance and rollout were managed by the internal digitalization team, which implemented repeatable KNIME workflows and control checks to support month end cadence and deviation review processes. The deployment reduced manual FP&A effort in Germany by shifting generation and transfer of narrative comments into automated flows, while preserving SAP BW as the source of record for variance calculations.
Lowe'S Retail 270000 $83.7B United States KNIME KNIME ML and Data Science Platforms 2019 n/a
In 2019, Lowe'S transitioned analytics workflows from Alteryx One Platform to KNIME as its ML and Data Science Platforms solution supporting Workforce Analytics and Workforce Management functions. The initiative was organized to deliver a comprehensive analysis of staffing challenges, formalizing a partnership between the Workforce Analytics and Workforce Management teams to align tooling with workforce planning objectives. KNIME was used to create visual data pipelines, data preparation and feature engineering workflows, and model prototyping capabilities consistent with ML and Data Science Platforms. Implementation emphasized reusable KNIME workflows for ETL orchestration, scoring pipelines, and experiment tracking to standardize analytics outputs across staffing and scheduling use cases. Operational coverage focused on workforce analytics and staffing analysis within Lowe'S broader workforce management function, with the Workforce Analytics team migrated onto KNIME tooling and products. The program included migration of analytic workflows from Alteryx One Platform to KNIME and training activities to transfer day to day analysis and pipeline maintenance to in house analytics staff. Governance activities centered on standardized workflow libraries, role based access controls, and process changes to centralize pipeline ownership within the Workforce Analytics organization. Release gates and documented pipelines were established to control analytics promotion from development into production and to ensure repeatable data preparation and model deployment processes.
Procter & Gamble Consumer Packaged Goods 108000 $84.0B United States KNIME KNIME ML and Data Science Platforms 2020 phData
In 2020, Procter & Gamble implemented KNIME to automate integration of complex manufacturing, lab, supply chain and quality data and to enable real time supply and demand forecasting and multi level dashboards. Procter & Gamble implemented KNIME, an ML and Data Science Platforms solution, to support supply chain and operations forecasting across global sites. The implementation centered on KNIME workflows for data ingestion, transformation, model orchestration and dashboarding, and on enabling citizen developer pipelines for rapid experiment to production cycles. KNIME was configured to host reusable ETL and model scoring components, and training paths were created to upskill roughly 8,000 citizen developers so they could operate and extend analytic workflows. The solution was developed in partnership with phData for supply chain and operations use and integrated manufacturing, laboratory, supply chain and quality data feeds to provide unified, multi level dashboards. Operational coverage was global and focused on enabling a single global decision meeting by consolidating regional views into a common set of real time indicators and forecasts. Governance emphasized centralized analytics stewardship and role based workflow handoffs to support the scaled citizen developer population, with phData supporting deployment and adoption. The rollout replaced multiple regional decision meetings with a single global decision meeting and shortened time to insight from hours to minutes.
Siemens Manufacturing 312000 $84.5B Germany KNIME KNIME ML and Data Science Platforms 2018 n/a
In 2018 Siemens deployed KNIME Analytics Platform through its Data Visions team to drive a data-citizen program across Manufacturing/analytics. The initiative began in January 2018 and targeted broad business adoption, ultimately reaching more than 3,500 business users across Siemens' manufacturing analytics organization and demonstrating enterprise use of KNIME within ML and Data Science Platforms. Implementation centered on KNIME Analytics Platform workflows configured for document ingestion, competitor PDF crawling, and text-mining, enabling nontechnical users to execute common analytic tasks. The deployment emphasized reusable workflow components and automation of end-to-end pipelines to reduce repetitive manual work and accelerate insight generation. KNIME workflows were scaled with RPA integrations across Siemens' global operations, creating automated handoffs between analytic processes and operational execution. Operational coverage focused on manufacturing analytics teams and adjacent business functions, with workflows provisioned for repeatable tasks to broaden self-service analytics. Governance was organized under the Data Visions team, which managed workflow lifecycle, access controls, and scaling policies while rolling out KNIME Analytics Platform across operations. The program produced explicit operational outcomes, including a reported reduction of approximately 30 hours per quarter through automation and wider analytic capability for thousands of business users.
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Buyer Intent: Companies Evaluating KNIME

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating KNIME. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating KNIME for ML and Data Science Platforms include:

  1. Katy Independent School District, a United States based Education organization with 2000 Employees
  2. Szabalyozott Tevekenysegek Felugyelti Hatosaga Hungary, a Hungary based Government company with 200 Employees
  3. American University of Sharjah, a United Arab Emirates based Education organization with 1500 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
Katy Independent School District Education 2000 $400M United States 2026-03-19
Szabalyozott Tevekenysegek Felugyelti Hatosaga Hungary Government 200 $8M Hungary 2026-02-02
American University of Sharjah Education 1500 $200M United Arab Emirates 2026-01-14
Media 3 $1M United States 2025-11-25
Utilities 106 $13M Germany 2025-07-03
Distribution 174 $104M Estonia 2025-04-04
Non Profit 2000 $500M United States 2025-03-04
Education 1000 $170M United States 2025-02-11
Insurance 34000 $46.4B United States 2024-08-19
FAQ - APPS RUN THE WORLD KNIME Coverage

KNIME is a ML and Data Science Platforms solution from KNIME.

Companies worldwide use KNIME, from small firms to large enterprises across 21+ industries.

Organizations such as Deutsche Telekom, Siemens, Procter & Gamble and Lowe'S are recorded users of KNIME for ML and Data Science Platforms.

Companies using KNIME are most concentrated in Communications, Manufacturing and Consumer Packaged Goods, with adoption spanning over 21 industries.

Companies using KNIME are most concentrated in Germany and United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of KNIME across Americas, EMEA, and APAC.

Companies using KNIME range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 100%.

Customers of KNIME include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified KNIME customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.