Zenarate Comparables

Find the most relevant public market comparables for Zenarate, including EV/Revenue and EV/EBITDA multiples to help you make informed investment decisions.

Company Overview

Zenarate is a leading SaaS provider of AI-powered skill-based learning and development for customer-facing agents. Their AI Coach™ platform uses AI to simulate customer scenarios, immersing agents in life-like conversation, screen, and chat simulations to improve customer experience and agent performance. They serve various sectors including financial services, healthcare, insurance, telecommunications, technology, and travel and hospitality.

Business Model

SaaS (Software as a Service) providing AI-powered simulation training for customer-facing agents.

Target Customers

Organizations with customer-facing agents, including financial institutions, healthcare companies, insurance providers, telecommunication companies, technology firms, and companies in the travel and hospitality industry.

Specific Focus

AI-driven simulation training for customer service and sales agents.

Location

Palo Alto, California

CEO

Brian Tuite

Industry

Software & services

Sub Sector

AI-powered Training and Simulation Software

3yr Revenue Growth

818%

Public Market Comparables

Below are the key valuation metrics for companies similar to Zenarate in the Software sector. These metrics can help you understand how the market values companies with similar business models and growth profiles.

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As a leading player in the Software & services industry within the Software sector, Zenarate operates in the specialized AI-powered Training and Simulation Software sub-sector. Understanding how Zenarate compares to its public market comps is essential for accurate valuation and strategic decision-making.

Our comprehensive analysis includes detailed comparables (compsets) featuring similar companies in the AI-powered Training and Simulation Software space, with complete financial metrics, growth trajectories, and competitive positioning insights that go beyond the surface-level data shown above.

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