As organizations race to deploy AI agents across their enterprises, they're encountering a critical bottleneck: fragmented knowledge bases and siloed agent capabilities that prevent comprehensive, cross-domain insights. This presentation explores how to address this challenge through a federated approach to enterprise agentic AI infrastructure. This session examines three fundamental challenges facing enterprise AI adoption: The Knowledge Fragmentation Problem: Organizations are independently building knowledge bases for specific use cases, leading to duplicated effort, inconsistent data parsing strategies, and context drift as source documents evolve. Each team creates their own chunking, embedding, and retrieval mechanisms without a unified architecture—resulting in AI agents that cannot access cross-functional domain knowledge or maintain accuracy at scale. The Agent Collaboration Gap: Today's AI agents operate in isolation within their domains. When business leaders ask complex questions spanning customers, pricing, services, and operations, they receive fragmented answers requiring manual synthesis. Without standardized agent-to-agent communication mechanisms, authentication frameworks, or centralized agent registries, organizations cannot deliver the holistic insights that drive strategic decision-making. The Governance and Innovation Paradox: Enterprises need to enable rapid experimentation while maintaining security, compliance, and user experience standards. Traditional centralized approaches stifle innovation; purely decentralized approaches create chaos. The challenge is building federated frameworks that guide discovery, assessment, incubation, and graduation of AI solutions without creating bottlenecks. This presentation introduces a three-pillar architecture for enterprise agentic AI: Unified Federated Knowledge Base: A bottom-up approach where domain teams create specialized knowledge bases that integrate into an organization-wide ecosystem through standardized ingestion pipelines, interfaces for vector databases and knowledge graphs, and evaluation frameworks for accuracy and relevance. Cross-Domain Agent Collaboration: Technical mechanisms enabling AI agents to discover, authenticate, and communicate with each other—transforming isolated data points into comprehensive business intelligence that spans organizational boundaries. Federated Innovation Framework: Secure sandbox environments with structured governance models that accelerate development time by 50% while maintaining enterprise standards for security and user experience. Attendees will learn: This session is essential for Chief Data Officers, enterprise architects, and data leaders navigating the transition from siloed AI experiments to scalable, federated agentic AI ecosystems that deliver measurable business value.
Dinesh Thangaraju
Head of AWS Data Platform, Amazon Web ServicesBreaking Down Data Silos: Building Federated Knowledge Infrastructure for Enterprise Agentic AI at Scale
Elena Alikhachkina
Chief Data and AI Officer, TE Connectivity
Danette McGilvray
President and Principal Consultant, Granite Falls Consulting, Inc.
Dr. John R. Talburt
Distinguished Professor of Information Science, UA Little Rock
Robert Abate
Senior Advisor, CDOIQ
Stuart Madnick
Professor & Founding Director, Cybersecurity at MIT Sloan (CAMS)
Mr. Yacura is the Founder of the International Association for Data Quality, Governance and Analytics. Prior to this, Mr. Yacura has served in several senior executive management positions at IBM, Pacific Bell, American Express, InterContinental Hotels Group, Bank of America, Information Services Group and most recently at Fannie Mae. Mr. Yacura has more than 30 years of supply chain experience and serves on various academic and professional advisory boards. Mr. Yacura earned his M.B.A. in Finance and M.S. in Accounting from Binghamton University and an M.Q.M. in Quality Management from Loyola University. He also graduated from the Senior Executive Program at Stanford University and has published over 50 articles on Supply Chain Management, Risk Management, Data Quality and Autonomous Intelligent Systems. Mr. Yacura currently serves as an Affiliated Graduate Faculty member at the University of Arkansas School of Information Science, visiting professor Bharath University (India) and has served as a lecturer at Sonoma State University in “Operations Research and Supply Chain Management” and is the co-author of the annual “Data Quality and Governance Study” conducted by N.C. State Poole School of Management. In addition, Mr. Yacura sits as a board member of the California Council for Excellence. Joseph Yacura, Vice Treasurer, California Council For Excellence
Daniel Pullen is currently the Chief Data Architect and Data Scientist for SAIC’s corporate data operation. SAIC is a fortune 500 Information Technology Services company based in Reston, Virginia. Currently, Daniel is leading the implementation of SAIC’s Cloud Native Data Platform that puts Data Management, Data Governance, Master Data Management and Cloud Native concepts at the forefront. Daniel Pullen started his journey in the realm of data through his education. He has three degrees in Information and Information Quality spanning from his B.S. of Information Science through his PhD in Integrated Computing: Information Quality Track. During his career in data, Daniel has participated in research and publications in both an academic and industrial capacities. He is passionate about data and how effective analytics can provide substantial value for organizations. Daniel always likes to highlight that modern Data Analytics through the application of comprehensive statistical models, machine learning and artificial intelligent are only successful through effective Data Management, Data Governance and Master Data Management. He has a rich background and experience in core data competencies including but not limited to Data Management, Data Governance, Master Data Management, Entity Resolution, Data Warehousing and Data Science. Entity Resolution was the topic of Daniel’s Doctoral Research at the University of Arkansas at Little Rock and his first exposure to the concepts of Information Quality. It will always be his first love when it comes to data! Daniel Pullen, Corporate Chief Data Scientist, SAIC
Dean C. Pickett is a seasoned private and public sector leader with a remarkable track record of driving enterprise data and predictive analytics divisions to new heights. With a wealth of expertise in Fortune 100 enterprise data strategies, IT and data operations, data management processes, and the oversight of large-scale analytics projects, Dean has consistently developed strategic vision and realized results. With his recent roles as leaders in Fortune 10 healthcare supply chain corporation and public sector, Dean has cemented his position as a true visionary and effective strategist in the corporate world. He currently serves as the Assistant State Chief Data Officer and Chief Data Officer at Department of Administrative Services for the State of Ohio. In this role, he is driving the effective use of data and maturing the analytics within the State of Ohio. Previously, he was an Executive Advisor and Program Lead for the InnovateOhio Platform – Data Analytics program at the State of Ohio, Dean helped drive the data and analytic maturity in Ohio. This is evident by the numerous national awards which the program has been awarded over the past 5 years. While in this role, Dean has helped to drive cost efficiencies, improve state revenue, improved the effectiveness of state programs, as well as helped in leading the efforts to reduce fraud across the state. Previously he served as the Managing Partner and Executive Advisor at Edge Analytics. In this role, he is accountable for strategic planning, business relationship cultivation, and revenue growth, which has demonstrated a remarkable increase of over 55% in the last two years. Dean is renowned for his effective leadership and ability to support enterprise operations. This is evidenced by his role as the Director of Data Analytics Platforms and Services for a Fortune 20 healthcare supply chain corporation. In that position, he successfully managed a $4 million project that involved transitioning information from Teradata to Hadoop, enabling greater insights and more accurate forecasting. Notably, he developed a dental management performance application and led initiatives to improve the analytic maturity across the State of Ohio, identifying areas for revenue improvement and program effectiveness. Additionally, he developed a cutting-edge dental management performance application, further solidifying his reputation as an innovator in the field. Dean’s career is marked by a relentless pursuit of excellence, a passion for analytics, and an unwavering dedication to driving innovation in the corporate world. Dean is also actively engaged as an advisory board member for several organizations, including Spring Labs, Plumlogix, Gramener, and Faith Life Church. Dean Pickett, Deputy State CDO, State of Ohio
Ashish is senior Data & Analytics Leader with more than 20 years of experience in Data Management, Analytics & Digital applications areas. He has orchestrated data strategy to envision and deliver data-as product for Deere, a Fortune 100 manufacturer and its Financial Services business; driven Data Governance and Management, fueled insight-driven decision-making cultures; and built high-flying data and data engineering platform teams from the ground up. He has worked and lived in 4 Continents (Asia, Europe, South America & North America) with experiences of developing and building Data and Digital Organizations across the globe. Notable accomplishments during Ashish’s prolific tenure at John Deere Enterprise (Deere) / John Deere Financial (JDF) include: Ashish Bajpai, Global Engineering Leader - Data & Analytics, John Deere
• Most recently as JD’s global Data Leader at Enterprise level, Ashish drove Enterprise Data Strategy, and launched and led data platform teams to deliver key data platforms in months (previously done in years) and led multiple major enterprise initiatives successfully (Unified data Platform, Enterprise Data Marketplace, Data Quality, and Enterprise Data Protection/Security) with a focus on active data/Metadata Management, data products and Data Governance
• Previously as Data leader for data and analytics products at divisional level, Ashish led multiple Data initiatives to transform John Deere Financial’s data into strategic products and established data teams (based on data mesh principles and aligned to business capabilities) across U.S., Europe, Asia, and South America, embedding agile scrum methodologies as key priorities.
Ashish has been awarded with 2 of the most esteemed company accolades at John Deere Enterprise—the 2020 Deere & Company’s Chairman Award and JDF President’s Award of Excellence.
• Transforming data into strategic assets during his 5 years as Data & Technology Head for John Deere Financial (JDF) in both South America and Asia, Ashish won Deere & Company’s Chairman Award and 2 JDF “President’s Awards” in 2016 and 2018 for driving strategic projects, including launching JDF India’s first global, mobile-based digital application that slashed credit approval time from 20+ days to less than 7.
• Assembling and steering a 100+ person data and technology team in India, Ashish launched the company’s first data and
analytics center of excellence (CoE).