Leveraging Machine Learning and IDP to Scale Your Automation Program

Scale Your Intelligent Automation Program

Join us for this 45 minute webinar to realize how to add scale to your intelligent automation program through just a touch of embedded ML for IDP.

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This FREE webinar was recorded on:
December 09, 2020
12:00 PM - 01:00 PM GMT

As document and input types get more and more complex, legacy business process automation technologies, like Robotic Process Automation (RPA), can struggle to keep up. Designed to execute precise rules and work with structured data inputs, these approaches lack the intelligence to handle the variability and ambiguity of diverse, real-world document processing workflows, making it a partial enterprise solution that needs to be supplemented with more intelligent technology. 

Fortunately, there’s a sea change coming to back offices, reshaping the way organizations operate. Leading IDP solutions that leverage the latest in Machine Learning continue to learn on the data they’re exposed to, complementing RPA solutions. 

Take your Automation Program to the Next Level

In this webinar we will explore:

  • How to leverage the latest developments in ML and AI to capture and categorise data from documents for further processing by other automation technologies
  • Differences between OCR and ML-driven automation solutions
  • The best approach to human-machine cooperation - how to design and implement a workflow incorporating both people and machines
  • Real-life stories where intelligent automation solutions speed up back-office operations, reducing errors and improving customer experience

Presenters:

Francisco Uribe
VP of Product
Hyperscience

As VP of Product, Francisco is responsible for managing Hyperscience’s product and design strategy and roadmap. Francisco has worked in the enterprise AI space for more than a decade. He founded BlackLocus, a data-driven startup that built an automated pricing engine for retailers, which was acquired by The Home Depot in 2012. After that, he spent 8 years working at Google in the Ads, Research and Cloud teams. Most recently he was head of the Perception AI team at Google Cloud responsible for Google’s computer vision and AutoML developer platforms.

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