We’ve been around this block for thirteen years now. We’ve built contact centres, watched companies invest heavily in new technologies and reinvent themselves again and again. And here’s what we’ve learned: the magic happens in your data foundation.
It’s not exciting, and it’s not shiny – but without it, your AI agents won’t know anymore than your table lamp does about how to actually process a refund in your OMS or truly resolve queries, end-to-end. AI is just the final stage of a many-stepped process in building a contact centre.
The Challenge Behind the AI Headlines
While businesses are busy evaluating GPT-4 versus Claude, the real challenge is often overlooked. Your customer data exists in multiple places simultaneously.
Orders live in your e-commerce system. Customer details sit in your CRM—mostly complete. Support tickets reside in your helpdesk platform. Product specifications inhabit some inventory tool that only a few team members fully understand.
When customers ask “Where’s my order?” it seems straightforward enough, but the complete answer requires information from several different platforms.
Your human agents have already mastered this complexity. They’ve become experts at navigating between systems, connecting information pieces, building complete customer stories. They’re essentially data detectives with excellent customer service skills.
AI agents need access to that same comprehensive information, but they need it in APIs.
We’ve Been Solving This Challenge Since 2011
Before AI agents became a priority, we were already working on the complex task of connecting disparate systems. We built workflows that can retrieve CRM data, pull order details from e-commerce platforms, check inventory levels, then present everything to human agents exactly when needed.
That infrastructure—the ability to gather data from existing systems and deliver it with proper context—remains incredibly valuable in our current AI-focused environment.
Your AI agents need exactly what human agents have always required: accurate information, delivered at the right moment, with appropriate context. The main difference? Instead of populating agent screens, we’re now feeding structured data to conversational AI that can interpret it for customers.
Your Systems Already Contain the Answers
Consider AI as an intelligent intermediary that excels at explaining complex information clearly. When someone asks about refund status, your AI doesn’t need to memorize your entire refund policy manual. It needs to check your refund system, understand current status and the implications, then communicate that information in an accessible way.
The same data pipeline serving human agents can effectively serve AI agents too – same integrations, business rules and trusted sources. It’s the interface the changes. Swapping browser tabs and user logins for secure, authenticated API requests and endpoints.
The trick to AI agents that work is accurate, real-time information from systems that actually run your business.
