KNIME is used in a wide variety of areas. We are providing a number of templates (or blue prints) for example applications for some of these areas below. We will keep adding to this list over time (and if you have an interesting addition, why don't you send us an email?). Note that on the KNIME Hub, you can also access wealth of workflows that demonstrate how to use some of the techniques, such as test and network mining in a more application agnostic way.
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KNIME Success Stories
Customer Success Stories highlight how a business problem or challenge was solved using KNIME Software and what value the company received as a result.
- Continental: Sparking Data Literacy with KNIME and Making Better Decisions
- Z5 Inventory: Leveraging Predictive Analytics Prevents $1.3 Million Worth of Medical Supply Waste
- BGIS: Quantifying Retrofit ROI using Natural Language Processing in KNIME
- Chiesi Farmaceutici: Automation of Physico-Chemical Properties Calculation and Registration using KNIME
- Combating Terrorism Technical Support Office: Applying Tensor Completion to the Study of Inter-State Competition and Irregular Conflict
- Siemens: Driving a Citizen Data Scientist Approach
- Forest Grove and AHG: Inventory Management in the Automotive Industry
- thaltegos: Automatic Invoice Checking
- thaltegos: Making Better Product Management Decisions
KNIME Innovation Notes
Innovation Notes provide the relevant background to a real application of KNIME Software. Each one is based on a fully working KNIME workflow, accessible via the KNIME Hub.
- Anomaly Detection
- Inventory Level Optimization
- Disease Tagging
- Recommendation Engine for Retailers
- Customer Sentiment Measurement
- Price Benchmarking
- Risk Information Extraction
- Automatic Expense Reimbursements
- Predicting Stock Value Changes
- Automated Workflow Testing and Validation
- Gene Expression Analysis with KNIME Analytics Platform
- Semantics and Ontologies with KNIME Analytics Platform
Other Customers Using KNIME
Here are some other examples of our customers and how they are using KNIME.