Session Presentations
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Keynote Presentation: AI in Private Equity: Building Intelligence into the Industrial Lower Middle Market
- Why PE firms have a structural AI advantage that most haven't yet operationalized, and how the constraints of smaller portfolio companies force a more pragmatic, outcome-first approach to AI deployment
- From raw portfolio data to decision intelligence: building an AI layer across a portfolio without enterprise-scale resources or a dedicated data engineering team
- Measuring AI ROI in a PE context: how to connect AI investment to hold period value creation, not just internal efficiency
Anurag Sachdev, Head of Data & AI, MAY RIVER CAPITAL
The Agentic Operating Layer for CX: Future-Proofing Financial Services Beyond the Chatbot
Enterprise conversational AI has moved through three eras: rule-based NLU that worked but couldn’t scale, the generative leap that changed what was possible overnight, and now the agentic shift, where AI doesn’t just understand the customer, it decides and acts. In financial services, the window to lead that shift instead of reacting to it is closing fast. In this session, Lanier Pegues (NiCE Cognigy) traces that evolution and unpacks what it takes to move from conversation-driven applications to a governed, agentic operating layer that’s built to last.
- Why this moment is a platform shift, not an upgrade cycle — and what “future-proofed” requires in a regulated, telephony-first environment
- The disintermediation risk most finance leaders are underwriting by accident: what happens when your customer’s AI agent replaces their browser session
- Moving from point solutions to orchestration — coordinating AI agents, human agents, and backend systems on a single data foundation
- Governance as the enterprise gate: not AI unleashed, but AI that’s supervised, accountable, and audit-ready — the difference between a pilot and a deployment
Keynote Presentation: Beyond the Chatbot: Parallelizing Agents for Speed and Scale
A single AI agent tackling a complex workflow hits the same bottleneck as a single engineer owning an entire system- it's slow, fragile, and doesn't scale. This talk makes the case for multi-agent architectures where specialized agents run in parallel, each owning a discrete subtask, coordinated by an orchestration layer. We'll cover how to decompose workflows into parallelizable units, manage inter-agent communication and dependencies, and handle failures gracefully.
Keynote Presentation: From Data to Strategy: Transforming Investment Processes with a Self-Correcting Multi-Agent Framework
- Traditional LLMs Are Not Production-Ready for Regulated Investment Workflows
- Harbor's Multi-Agent AVR Framework Delivers Institutional-Grade Reliability
- Validation-Centric AI Is Essential for Scalable Adoption
Shuen Mei, VP, Director of Software and Data Engineering, HARBOR CAPITAL
Keynote Presentation: Agentic (AI) Master Data Management
- Transforming MDM with autonomous AI agents
- Improving data quality and governance through intelligent automation
- Enabling trusted, scalable AI with unified enterprise data
Raghuvaran Reddy Kalluri, Lead Developer & Solution Architect, ROYAL BANK OF CANADA