Cekura

Product Introduction

1. Cekura is an end-to-end quality assurance platform designed for Voice and Chat AI agents, providing pre-production testing, scenario simulation, and production call monitoring to ensure reliability across development stages. It enables conversational AI companies to validate agents using AI-generated datasets, custom workflows, and real audio inputs while offering actionable evaluations.
2. The core value of Cekura lies in its ability to accelerate deployment timelines, reduce operational risks, and maintain compliance by systematically identifying failures in conversational logic, compliance gaps, and performance bottlenecks before and after deployment.

Main Features

1. AI-Driven Scenario Simulation: Cekura generates synthetic test scenarios using AI models and custom datasets, simulating diverse user personas (e.g., impatient customers) and edge cases (e.g., compliance-critical interactions) to validate agent responses. Tests are executed in parallel, enabling rapid evaluation of thousands of scenarios in minutes.
2. Real-Time Production Monitoring: The platform provides observability tools with real-time dashboards, detailed call logs, and trend analysis to track metrics like intent accuracy, latency, and compliance adherence. Automated alerts notify teams of errors, performance drops, or regulatory violations for immediate remediation.
3. Workflow-Centric Testing Frameworks: Users define custom evaluation criteria (e.g., appointment cancellation success rates) and replay historical conversations to validate agent updates. Integrations with voice platforms allow direct deployment of tested agents while maintaining audit trails for compliance reporting.

Problems Solved

1. Manual Testing Inefficiency: Traditional QA processes for voice agents require manual script execution, which is time-consuming and fails to scale for complex, dynamic conversational flows. Cekura automates scenario generation and parallel testing, reducing validation cycles from weeks to hours.
2. Unreliable Production Performance: Post-deployment issues like unexpected user interruptions or compliance oversights often go undetected until customer complaints arise. Cekura’s monitoring detects anomalies in real time and provides root-cause analysis using granular call logs.
3. Compliance-Critical Use Cases: Industries like healthcare and finance require strict adherence to regulatory protocols (e.g., data privacy, scripted disclosures). Cekura pre-tests agents against compliance checklists and flags deviations during simulations or live calls.

Unique Advantages

1. Integrated Pre-Prod and Prod QA: Unlike siloed testing or monitoring tools, Cekura unifies both stages, allowing teams to reuse test scenarios for ongoing monitoring and compare results across environments.
2. Persona-Based Stress Testing: The platform simulates high-pressure user behaviors (e.g., frequent interruptions, accented speech) using AI-generated audio and text inputs, replicating real-world stress conditions unavailable in basic testing tools.
3. Enterprise-Grade Security and Scalability: As a SOC2 Type 2 compliant platform backed by Y Combinator, Cekura supports large-scale deployments with role-based access controls, audit logs, and integrations with enterprise LLM providers like Cisco’s Webex AI agents.

Frequently Asked Questions (FAQ)

1. How quickly can Cekura integrate with existing voice agent platforms? Cekura supports API-based integrations with major conversational AI platforms, enabling deployment in under an hour. Pre-built connectors for Twilio, Retell AI, and Cisco Webex simplify setup.
2. Does Cekura support compliance testing for industries like healthcare? Yes, the platform includes pre-configured compliance templates (e.g., HIPAA disclosure checks) and allows custom rule creation to validate regulatory adherence during simulations and live calls.
3. Can Cekura test agents in multilingual or accented speech scenarios? The platform generates synthetic audio with diverse accents and languages, and users can upload real voice samples to create region-specific test cases for global deployments.
4. How does Cekura handle false positives in alerting? Alert thresholds are customizable, and the system uses contextual analysis (e.g., intent misclassification vs. transient network errors) to reduce noise. Teams can review flagged calls via the dashboard for confirmation.
5. Is historical data retained for audits? All test results, production call logs, and evaluations are stored with versioning, enabling compliance audits and retrospective analysis of agent performance trends.