Modern chatbots rarely follow a single path. Real users interrupt, change topics, or revisit earlier details, and your testing framework should be able to keep up.
Cekura enables teams to evaluate chatbot performance across entire conversation sequences, not just isolated messages, ensuring that agents maintain accuracy, coherence, and context through every turn.
Sequence-Level Testing
Cekura treats a dialogue as a complete exchange - user ↔ bot ↔ user ↔ bot - instead of testing one message at a time.
Teams can auto-generate or author full conversation scripts, simulate diverse user personas, and replay those dialogues across model versions or environments to validate continuity and flow.
Context Retention & Branching
When users shift topics, ask clarifying questions, or interrupt, Cekura verifies whether the chatbot remembers earlier inputs and adapts correctly.
Its response consistency and hallucination metrics evaluate memory carryover, while custom scenarios test branching logic, interruptions, or clarifications to catch subtle context-loss failures.
Scenario Management & Version Control
Cekura’s scenario engine stores and versions multi-turn test cases so QA teams can re-run the same flows after every model, prompt, or API update.
Through its API and CI/CD integrations, these tests can be triggered automatically on every code push, maintaining a reliable regression baseline.
Automated Metrics & Continuous Evaluation
Each run is scored on built-in metrics such as:
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Turn relevance and task completion
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Response consistency and relevancy
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Latency, interruption handling, and repetition
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CSAT and sentiment
Teams can also define custom LLM-as-a-judge metrics or connect their own models for specialized evaluation. Automated regression and drift tracking highlight where conversational quality changes over time.
Channel & Environment Coverage
Multi-turn testing in Cekura runs seamlessly across chat interfaces, SMS, and voice channels - letting teams ensure consistent experience regardless of delivery medium.
Native integrations with platforms like Bland, Vapi, Retell, Pipecat, ElevenLabs, and LiveKit make setup nearly frictionless.
Scalability & Monitoring
Cekura runs parallel simulations across hundreds of conversation paths, surfacing drop-offs and context errors quickly.
Teams can benchmark multiple models (e.g., GPT-4o vs GPT-5 vs Gemini) on identical test suites and visualize comparative scores via dashboards with turn-level timestamps and performance trends.
Why It Matters
Multi-turn testing reveals how your chatbot behaves in the only place that truly matters: live conversation.
Cekura automates what once required hours of manual QA, turning conversational reliability into a measurable, repeatable process.
With each iteration, you know exactly how your chatbot performs across turns, branches, and contexts, before your users ever notice a flaw.