Oct 9, 2019
Registration and Opening
As part of ATARC’s AI Working Group RPA Project Team, this series of RPA industry engagements will enable attendees to hear capability presentations and marketplace trends from RPA vendors, learn industry perspectives and best practices for RPA exploration, adoption, and implementation in the public sector, and ask questions, network, and build collaborative industry-government partnerships in an intimate setting.
IRS Special Assistant, Mitch Winans, will brief the audience on the Robotic Process Automation Project Team within ATARC’s Artificial Intelligence Working Group.
Special Assistant, IRS
This presentation will address conversational RPA capabilities in the market today and their applications in the public and private sector. Evan will highlight the technological components of conversational RPA, common use cases, the business goals most often associated with their adoption, and ways in which these solution sets may evolve in the years ahead.
Chief Business Officer, Pypestream
10 Minute Break
The Marriage of RPA and NLP
This presentation addresses the information management challenges facing Government and the use of NLP and RPA layered approaches to improve compliance, reduce risk and increase understanding of data.
Chief Technology Officer, Savan Group
Using Machine Learning and Expert Input for Automation of Entity Resolution, Ontology Development, Record Duplication, and Categorization
Tamr connects and integrates information sources siloed across the enterprise to deliver data that is up to date, accurate and unified across a myriad of sources. Tamr uses machine learning and expert input for automation of entity resolution as well as ontology development, record deduplication and categorization. For RPA initiatives Tamr provides an intelligence layer to extend the degree of automation by resolving key entities within the data. DHS, DoD and the IC use Tamr to: (1) improve decision making with more granular, accurate and complete data; (2) build compelling business metrics since all data has become usable; and (3) improve the adoption process improvement through an increase in the quality of the information.
Federal Team Lead, Tamr