Artificial intelligence is changing how financial firms operate, analyze data, and build software products. But behind the excitement lies a complex reality: successful AI adoption depends on strong data strategy, disciplined product development, and close collaboration with customers.
In this exclusive interview with Lead the Machine, Allvue Systems’ Chief Product and Marketing Officer, Ivan Latanision joins host Kirstin Marr, Founder and CEO of Lead The Machine, to explore how AI is transforming private markets, what it takes to build AI-ready platforms, and how technology leaders can turn AI innovation into real value for clients.
Ivan and Kirstin previously worked together at Insurity, a leading software provider for insurance companies, where they intentionally collaborated on how software and analytics could come together to create better outcomes for customers. During Ivan’s time at Medidata, where he joined as Head of Product, Ivan led a strategy to bring together roughly 40 separate products into a unified platform. To guide the transformation, he created a customer advisory board that mapped the full clinical trial lifecycle and helped surface pain points across clients’ technology environments. Today at Allvue Systems, Ivan is tackling this challenge by building the data infrastructure needed for AI-powered products. Instead of expecting clients to manage complex data integration themselves, he focuses on defining common data models and bringing together data from multiple sources so it can be structured, normalized, and ready for AI-driven insights.
“At Allvue, we’re building, we’re defining data models, and we’re defining ways to bring data in and master data so that we have a common model that AI can understand.”
– Ivan Latanision, Chief Product and Marketing Officer, Allvue
Key themes discussed:
- Building AI-ready platforms with strong data foundations
- Monetizing AI in enterprise software products
- Customer advisory boards as strategic product tools
- Embedding AI into workflows rather than standalone features
- Practical AI use cases such as document extraction and automation
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