Omilia Launches Self-Learning Agentic CX Platform for Enterprises

As enterprises look to move beyond scripted automation and fragmented customer experience tools, Omilia has introduced a new platform aimed at redefining how AI operates in customer service. The launch of the Omilia Self-Learning Agentic CX platform marks a significant development for the MarTech and CX technology ecosystem, promising autonomous improvement, faster deployment, and enterprise-grade governance across voice and digital channels.

Omilia announced the platform as the world’s first enterprise-grade, self-learning Agentic CX solution. Designed to autonomously understand, optimize, and improve customer conversations, the platform moves away from traditional orchestration models that rely on stitched-together chatbots, brittle natural language systems, and heavy manual tuning. Instead, Omilia positions its new system as a unified AI workforce capable of continuous learning from real interactions.

For years, advanced CX AI has often required long implementation cycles, significant professional services, and ongoing operational overhead. Omilia said the new platform changes that dynamic by enabling organizations to deploy autonomous CX agents with zero days to go live. The system does not require predefined intents, training datasets, or complex flow diagrams, relying instead on zero-shot routing, voice-native intelligence, and autonomous task planning.

“This is our moon landing for enterprise CX and a direct response to market demand,” said Claudio Rodrigues, Chief Product Officer at Omilia. He noted that CX teams have historically been forced to choose between experimental LLM tools, hyperscale AI offerings that lack precision, or orchestration platforms that create fragile stacks.

Dimitris Vassos, Co-Founder and Chief Executive Officer of Omilia, added that superficial integrations marketed as flexibility often undermine real optimization. “When core AI capabilities are treated as interchangeable commodities rather than deeply engineered systems, optimization never happens and production performance collapses outside of controlled demos,” he said.

The Omilia Self-Learning Agentic CX platform is engineered across every layer of the CX stack, including speech recognition, reasoning, routing, workflow execution, analytics, and self-learning. Built with regulated industries such as financial services and healthcare in mind, the platform is designed to support high-volume, mission-critical customer journeys while maintaining explainability and auditability.

A key differentiator is continuous self-adaptation. Omilia agents observe both human-led and AI-led conversations, extract best practices, test improvements through simulation, and deploy optimizations under human oversight. The company said this closed-loop learning system allows agents to improve safely and autonomously over time. Performance benchmarks cited by Omilia include high voice accuracy, strong chat containment, and high task completion rates from day one.

The platform also allows organizations to control how quickly they adopt autonomy. Enterprises can move from deterministic workflows to hybrid and fully agentic CX models within a single governed environment, with every decision remaining transparent and observable.

“Today marks the end of static CX, the end of orchestration-heavy design, manual NLU maintenance, expensive tuning, and legacy IVR,” Vassos said.

For enterprises evaluating the future of customer experience, the Omilia Self-Learning Agentic CX platform signals a broader industry shift. As AI moves from assistance to autonomy, platforms that combine self-learning, governance, and enterprise readiness are likely to define the next generation of scalable, trustworthy CX automation.