Cekura is a platform built for teams that automates quality assurance for voice and chat AI agents. It allows teams to simulate real-world conversations featuring diverse personas, accents, and edge cases, then evaluate agent performance using custom metrics. From pre-production testing and adversarial red teaming to live production monitoring with Slack alerts, Cekura covers the full agent lifecycle. It integrates directly into CI/CD pipelines so that every prompt or model change is regression-tested automatically.

• Automated Scenario Generation: Create hundreds of test cases from your agent's prompt or workflow description, covering happy paths, edge cases, and adversarial inputs automatically.
• Custom Persona Simulation: Test against 50+ specialized personalities including non-native speakers, impatient users, and terse responders, with varied accents and background noise for voice agents.
• Multi-Turn Conversation Evaluation: Validate full conversational arcs with branching logic, interruptions, and tool-call verification, not just single-turn accuracy.
• Red Teaming at Scale: Run thousands of adversarial simulations in minutes, probing for jailbreaks, prompt injection, bias, toxicity, and PII leakage across multi-turn attacks.
• Production Monitoring & Alerts: Track live calls and chats for drop-offs, missed intents, latency spikes, and instruction failures. Get alerts in Slack before customers complain.
• CI/CD Pipeline Integration: Trigger regression tests automatically on every code push, prompt change, or model swap to prevent production breakdowns.
• A/B Testing & Model Comparison: Compare prompts, models, or infrastructure versions across 30+ calls with detailed metrics on success rates, latency, and talk ratio.
• Actionable Prompt Recommendations: Get specific suggestions tied to exact conversation turns to improve each tracked metric.

• Significant Time Savings: Cuts QA testing cycles from weeks to minutes by automating scenario generation and evaluation at scale.
• Platform-Agnostic: Works with Dialogflow, Lex, Rasa, Botpress, Retell, Vapi, LiveKit, ElevenLabs, and custom pipelines, so you don't need to change your stack.
• Developer-Friendly CI/CD Integration: Fits naturally into existing development workflows with API access and automated regression testing on every push.
• Real Production Insight: Failed real-world calls can be converted into new test cases, turning actual user issues into future regression checks.

• Specific Niche Focus: Built specifically for conversational AI QA, so it won't help if you need general software testing or non-conversational AI evaluation.
• Limited Pricing Transparency: Enterprise pricing requires contacting sales, making it hard to budget without a conversation first.
• Learning Curve for Custom Metrics: Setting up advanced custom evaluators and metric frameworks takes time and technical effort to configure properly.

• Pre-Deployment Voice Agent Validation: Before launching a customer-facing voice agent, run hundreds of simulated calls with diverse accents, background noise, and edge-case behaviors. Catch failures in scheduling, escalation, or tool-call logic before real users encounter them.
• Healthcare Compliance Testing: Validate that your AI agent follows HIPAA-compliant conversational flows, handles patient data correctly, and includes required disclaimers. Confido Health used Cekura to verify end-to-end accuracy of appointment scheduling and insurance verification workflows.
• Infrastructure Migration Stress Testing: When switching calling platforms or upgrading models, run full-scale stress tests simulating thousands of calls. Compare key metrics between old and new stacks to deploy with confidence, as Confido Health did during their infrastructure migration.
• Ongoing Production Monitoring for Contact Centers: Monitor live agent interactions across your contact center for sentiment drops, latency spikes, and missed intents. Receive Slack alerts when critical metrics fail so your team can intervene before issues escalate.
• Red Teaming Before Enterprise Rollout: Before deploying in regulated sectors like banking or insurance, run adversarial simulations to probe for prompt injection vulnerabilities, PII leakage, bias, and toxicity. Multi-turn attack simulations expose weaknesses that single-turn tests miss.
• Regression Testing in CI/CD for AI Teams: Integrate Cekura into your development pipeline so every prompt change or model update triggers automated tests. Prevent regressions in cancellation flows, reschedule workflows, or compliance checks without manual QA effort.