Zenarate Introduces Evolve Platform to Unify Human and AI Frontline Performance

Jun 25, 2026
Zenarate has announced Evolve, an agentic conversational AI platform that brings human and AI agent training, governance, and performance management into one system for customer service teams.

Zenarate announced in a press release the launch of Evolve, an agentic conversational AI platform designed to unify how enterprises manage human and AI frontline performance. The platform enables organizations to automate, validate, and improve customer interactions across voice and digital channels within a single framework.

Evolve provides non-technical teams with tools to design, test, and optimize AI agents using the same business logic, brand standards, and performance metrics applied to human agents. It allows enterprises to determine when AI can make autonomous decisions and when actions remain governed by code, offering greater control over customer engagement design and quality management.

Evolve extends Zenarate’s Frontline Performance Platform, joining its existing Perform and Analyze capabilities. Together, these components create a closed-loop system that connects AI agent automation, coaching, and performance analytics, enabling continuous improvement across both human and AI teams.

The company will showcase Evolve at Customer Contact Week, highlighting how the platform supports a unified approach to human and AI performance in customer service environments.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief, Sales & Marketing AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.