How prepared is your data to power AI models and agents (internally or customer-facing)?

We’re experimenting with AI, but our data is mostly batch and siloed; it’s hard to plug into models.We can push some curated data sets into cloud data warehouses or models on a scheduled basis.We can stream real-time, governed first-party data into multiple AI services and models.We treat our platform as an AI data layer: real-time, consented, and optimized for agents and models via APIs, functions, and “invoke your own model” patterns.

Can you serve AI agents and applications with fresh, compliant context?

Not yet. We don’t have a clear way to serve agents directly from our digital interfaces.We can manually expose some APIs or data feeds, but it’s not systematic or governed.We’re starting to design an “agentic front door” that exposes compliant, high-quality data to AI agents.We have or are actively building a dedicated agentic interface – serving real-time, high-signal profiles and events to agents, with consent, governance and performance built in.