Nimbus AI: Conversational AI Evaluation for Chatbots and Voicebots
Measure whether the conversation succeeded, not whether each turn looked good.
Automated evaluation of chatbots, voicebots and rule-based bots
Chatbot testing checks single answers. Conversational AI needs more: the same prompt can return different answers, users switch topic mid-conversation, and one unsafe or non-compliant reply can undo the trust. A bot that passed testing at launch can also drift as its knowledge base and model change.
Nimbus AI generates test datasets from your own knowledge base and requirements, or, where no knowledge base exists, builds custom test cases from websites and other public sources. It connects through your bot’s API or UI to test guardrails automatically, and scores every conversation on 60+ checks, from hallucination and grounding to bias, privacy and compliance.
Deliverables
Here is what teams gain from Nimbus AI, drawn from client programs.
Efficiency
Automated test generation and evaluation reduce manual effort, and your team reviews insights instead of writing scripts.
Speed
Run evaluations without complex setup. Results arrive in minutes, which speeds up reviews and iterations.
Trust
See how your bot performs on fairness, transparency and accessibility, with clear, actionable feedback across safety, ethics and usability.
Global readiness
Nimbus AI supports multiple languages, including the most widely spoken Indian languages and Arabic, and regional compliance needs, which suits enterprises with global and regulated deployments.
Adaptability
Nimbus AI adapts to updates in your knowledge base, LLM advances and smarter evaluation strategies.
Reliability
Find performance regressions before they reach customers, and keep your bots consistent and trustworthy.
Why Nimbus AI?
The capabilities below are the ones teams rely on most in day-to-day use.
Automated test generation
Nimbus AI generates questions and expected answers from your source material, runs them against your bot and scores every response.
QK golden datasets
Evaluate against QKTech’s proprietary golden datasets, built from 26 years of testing experience across banking, insurance, healthcare and automotive.
AI test design from requirements
Turn BRDs, FRDs, user stories and process documents into positive, negative, boundary and exception test cases, each traced to its requirement.
60+ named evaluation checks
Answer correctness, answer and context relevance, hallucination, grounding, RAG quality, bias and fairness, privacy, jailbreak and robustness.
Multi-turn conversation testing
Beyond independent test cases and scenarios, Nimbus AI runs multi-turn conversations: it asks about a topic, then follows up with three or four related questions, and evaluates how well your bot handles context, memory and changing user intent.
Custom metrics for your domain
Build LLM-based or Python-based custom metrics. We shape them from what we see in production, such as repeated paraphrasing, sentiment that doesn’t fit the moment and multi-intent handling.
Automated evaluation workflow
Continuous, automated evaluation cycles replace manual QA and spreadsheets, turning days or weeks of manual testing into hours or minutes.
Re-evaluate after every change
Re-run evaluations after knowledge-base, model or chunking changes to confirm quality improved, not just changed.
Insightful reports
See what went wrong and what worked in each run, through metrics, transcripts and graphs. Multidimensional scores, the exact failing turn and regression history across releases mean go/no-go decisions rest on evidence.
Admin dashboard
Admins see evaluation results and insights for their bots in one dashboard.
Evaluate voicebots, not just transcripts
Customers are moving from typing to talking. A voicebot can return a perfect transcript and still fail the call. Nimbus AI checks whether the whole voice conversation worked, not just the words.
Latency
Long pauses make callers hang up. Nimbus AI measures end-to-end response time across the voice journey.
Interruptions
Callers talk over bots. Nimbus AI checks whether the bot stops, listens and keeps the context.
Pronunciation and read-back
Account numbers, dates of birth and policy IDs have to be read back correctly. Nimbus AI flags any mismatch.
Tone
A cheerful reply to a fraud report is still a failure. Nimbus AI checks whether confidence and sentiment fit the moment.
Caller diversity
Accents, emotions, speaking speed and background noise, across the most widely spoken Indian languages, including Hindi, Tamil and Marathi, as well as Arabic.
Caller personas
Test with personas such as a slow speaker, an older caller, an angry or frustrated customer, or someone calling from a noisy place. No single manual tester can emulate that range.
Test cases from real calls
Upload transcripts of past calls, or the audio recordings themselves, and Nimbus AI turns them into test cases.
Root cause
See whether a failure came from speech recognition, the bot’s reasoning or its spoken output, so teams fix the right layer.
Deploy your way, on-premise or cloud
On-premise: zero data egress, auditable and fully traceable. Built for regulated teams that cannot send data outside their environment.
Cloud: elastic scale for large test suites, with the same requirement traceability and reporting.
Insights
Nimbus AI in Action
These engagements show Nimbus AI at work in client programs.
Success Stories
Insights
Challenges we’ve solved for our clients
Success Stories
Leading Thoughts
Common questions about Nimbus AI
What is Nimbus AI?
Nimbus AI is a QKTech platform that evaluates GenAI chatbots, voicebots and rule-based bots. It generates test questions from your knowledge base and scores each answer on dimensions such as accuracy, safety and fairness, across whole conversations.
How do you evaluate an LLM chatbot?
We generate questions from the bot’s own source material, run them against the bot and score the answers for accuracy, safety, fairness and other dimensions. Repeat runs show whether quality holds after changes.
How does Nimbus AI test conversations?
It runs multi-turn conversations, asking a question and then three or four follow-ups on the same topic, and checks how the bot handles context, memory and changing intent across turns.
Can Nimbus AI detect regressions after a model or knowledge base update?
Yes. Nimbus AI tracks scores over time and flags a drop before customers see it.
Evaluate your bots with Nimbus AI
Run real evaluations and see what Nimbus AI can do for your AI stack.