Vocera AIAutomated testing and monitoring platform for voice AI agents

4.3 (4)

Reviewed by Daniel Nikulshyn·Updated July 2026

Overview

Cekura, also known as Vocera AI, is an automated testing and monitoring platform for voice AI agents. It allows users to launch voice evaluations before going live, then monitor real production calls and continuously improve with intelligent feedback. The platform integrates with various conversational AI tools and provides end-to-end testing and observability for conversational AI. It offers features such as simulating scenarios, testing prompt changes, and monitoring voice-specific quality signals. Cekura is used by over 70 conversational AI companies across the globe and provides a range of tools for testing, monitoring, and improving voice AI agents.

Key features

Simulated voice agent test calls
Custom evaluation criteria and scoring
Real-time production monitoring and alerts
Conversation transcripts and analytics
Regression testing across agent versions
Failure detection for hallucinations and errors

Pricing

Model: Freemium
Category: Task automation
Rating: 4.3 / 5 (4)

Use cases

Testing Voice AI Agents

Cekura allows users to test voice AI agents with various personalities and evaluate based on their needs. The platform provides features such as simulating scenarios, testing prompt changes, and monitoring voice-specific quality signals.

Monitoring Production Calls

Cekura enables users to monitor real production calls and continuously improve with intelligent feedback. The platform provides features such as voice observability, detecting voice quality issues, and real-time alerting.

Improving Voice AI Agents

Cekura provides tools for improving voice AI agents, including optimizing LLM judges, tracking production metrics, and building custom plot layouts. The platform also offers features such as conversation analytics and user insights.

Pros & Cons

Pros

Scenario-based simulation of real call flows
Continuous monitoring of production voice agents
Detailed evaluation metrics and transcripts
Catches regressions before deployment

Cons

Focused only on voice agents, not broader chat AI
Requires setup of test personas and criteria
May need integration work with existing stacks

Reviews

4.3

Average from 4 ratings.

Liam O’Connor

Mar 25, 2026

Use it every day

Honestly didn't expect to like it this much. Failure detection for hallucinations and errors is exactly what I needed, and catches regressions before deployment. I do wish requires setup of test personas and criteria, but I reach for it almost every day now and it just clicks.

Ethan Brooks

Mar 12, 2026

Years in this space

I've evaluated a lot of these over the years. What stands out here is conversation transcripts and analytics — handled better than most — and continuous monitoring of production voice agents. Requires setup of test personas and criteria is my one real gripe. Worth the time if this is your use case.

Nadia Petrova

Mar 6, 2026

Years in this space

I've evaluated a lot of these over the years. What stands out here is real-time production monitoring and alerts — handled better than most — and scenario-based simulation of real call flows. May need integration work with existing stacks is my one real gripe. Worth the time if this is your use case.

Esther Adeyemi

Dec 3, 2025

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on custom evaluation criteria and scoring, and continuous monitoring of production voice agents caught me off guard. still, I'd recommend giving it a real trial.