Listen now on your favorite streaming service!
presented by KeyMark
Summary
Ed sits down for a conversation with Matisha Ladiwala, Vice President and General Manager for Hyland’s Content Intelligence Cloud (CIC), to discuss building, governing, and deploying domain-specific agents. They cover how governance helps AI pilots succeed through trust, and dig into Hyland’s federation strategy, the agent mesh architecture, MCP as a semantic layer, and domain-specific knowledge graphs.
Discussion includes:
- Why enterprise AI adoption stalls at the pilot phase
- Extending governance trust to agentic AI
- Combining structured data from systems of record
- Multi-agent orchestration across platforms
- MCP (Model Context Protocol) as a semantic bridge connecting agents and endpoints
- Agents focused on business outcomes
- Graphing industry-specific knowledge to improve agentic time-to-value
Answered questions:
- Why do most enterprise AI pilots fail to reach production?
- What is an agent mesh, and how does it work in enterprise AI?
- How does MCP connect AI agents across different platforms?
- What is data federation in the context of enterprise content management?
- How does Hyland’s CIC handle AI governance for regulated industries?
- What is an enterprise context engine, and how does it power agentic AI?
- How do industry-specific knowledge graphs accelerate AI deployment?
Enterprise IT leaders, AI program owners, or AI architects are under immense pressure to make sense of an industry where new terms come out of the woodwork every weekend. This is a great conversation to help these job roles think through pilot projects and build trust in focused, calibrated AI agents.
