Continuously grow your automation ROI.
Make every
automation count

Drive sustainable ROI by selecting the right processes to automate, based on AI-driven data collection, analysis and recommendation.

Create automations
in a click

With a click of a button, the recommended process sequences are seamlessly converted into active automation flows.

Create a steady stream of efficiency opportunities

Installed as part of the NEVA desktop bot license, Automation Finder continuously maps and prioritizes processes, providing an endless source of automation opportunities.

A key success factor in your automation journey.

Gain full confidence and understanding for which processes will contribute most to your automation success, when automated.

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Intelligent, fact-based automation pipeline discovery.

Selecting the right processes to automate with process bots is a critical step towards ensuring Robotic Process Automation (RPA) project success and driving sustainable ROI. However, with so many processes across different organizational divisions, it is challenging and very time consuming to pinpoint the most appropriate processes based on manual analysis and subjective human judgement.

Automation Finder, a task mining solution, is included with NEVA, NICE’s attended automation solution. It helps the enterprise COEs to identify automation candidates based on unsupervised machine learning algorithms and an accurate scientific approach.

Introducing your ROI booster.

Intelligent identification of process automation opportunities to maximize ROI.

communication
"NICE Automation Finder is a powerful tool, providing amazing discovery and analysis, which greatly improves how we uncover automation opportunities.”
Large EMEA Telco
The path for intelligent automation discovery.
Data
collection
Collects and analyzes large amounts of employee desktop data, comprising user actions such as keystrokes, mouse selections, applications used, pages visited, field entries, handle time, and more. The data is handled securely with the option to anonymize specific applications and data types for security purposes.
Unsupervised & semi-supervised machine learning
Uses unsupervised machine learning to interpret and translate the screen events into meaningful sequences which can then be clustered and labeled for easy identification. It then uses semi-supervised ML for inputting the business analyst’s insights back into the prioritization learning process.
Categorization and prioritization
Identifies process sequences and variations, performed by employees, based on several parameters, such as: no. of users, frequency, process handle time and manual action types. The opportunities are scored and prioritized according to their ROI potential for automation, and presented in a dashboard report.
Click to automate & document
Automatically generates working automation flows in the design tool and design documentation, all with a click of a button, dramatically reducing the hand off time from the business analyst to the developer and creating a documentation repository.
Contact us

If you would like to know more about our platform or just have additional questions about our products or services, please submit the contact form. For general questions or customer support please visit our Contact us page.

Blog

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Enterprises need to choose between various approaches to automation discovery and decide which is better suited for their needs, as well as what it required to successfully use each technology (or both).

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The science behind automation discovery

Learn the science behind NEVA Finder and how it should be executed to maximize automation process deployment.