Omilia

Containment plateaus for one reason: your automation stopped learning the day it went live. Omilia's Self-Learning Agentic CX learns from every call, spots what to automate next, and builds the agent itself. Your team approves it. It launches. 90%+ call resolution. Up to 78% lower cost per interaction. ROI in around three months.

Every percent of containment you miss costs you again and again. Traditional automation decays. Self-learning agentic CX doesn't. It analyzes every interaction, improves it, and even builds new agents, all with human approval at every step. 90%+ call resolution. Up to 78% lower cost per interaction.

Customers don't escalate because they prefer agents. They escalate because your self-service didn't understand them. Omilia's AI Service Agents don't trap people in menus. They understand what the customer needs and act across your systems to resolve the request. It's why Discover, Taco Bell and Purolator trust Omilia with their customer service.

The board asked for AI in the contact center. You have to make it survive real calls. LLMs are great at spotting patterns after the fact, but they're not built for a live call: real-time, noisy, accented, no room for a delayed answer. Omilia is purpose-built for synchronous voice, with zero hallucinations and a full audit trail baked in.

'Press 1 for account services' isn't self-service. It's a queue with extra steps. Customers abandon it, NPS slides, and the contact center gets written off as a cost center. Omilia's AI Service Agents understand intent in natural speech and complete the task. Completion rates rise, NPS recovers, and the cost center argument goes away.

Your best agents resolve the hard calls and rarely needs a second attempt. Everyone else is somewhere behind them. Omilia analyzes 100% of your interactions, learns what your strongest people do, then builds AI service agents that work the same way on every call. Self-improving. Never unsupervised.