Chatbot Testing Services

The problem

Chatbot testing is not “type three questions and screenshot the widget.” Users interrupt, change topic, paste error codes, ask the same thing twice, and expect the bot to remember what they said four turns ago. Voice adds barge-in, noise, and failed speech-to-text.

This page is conversation-path QA. If the bot’s job is mostly to call tools, use AI agent testing. If it answers from a knowledge base, add RAG evaluation.

What’s at risk

• Context dropped mid-conversation
• Contradictory answers across turns
• Dead-end loops with no escalation
• Containment that never hands to a human
• Voice flows that work in a quiet office and fail on a phone

What we test

• Happy paths and the ugly ones (typos, mixed language, partial account numbers)
• Multi-turn context and topic switches
• Fallback, clarification, and human handoff
• Tone and policy (what the bot must not promise)
• The product around the bot: login, tickets, the page the widget sits on
• Voice: turn-taking, interruption, repeated confirmation

See how we think about conversational flows. Parent: AI testing services.

How we work

1. Map the intents and the journeys that matter commercially
2. Write conversation scripts and leave room for exploratory chat
3. Run them on the real widget or voice channel, not only an API playground
4. Re-run after prompt, NLU, or flow-builder changes

Deliverables

• Conversation scenario set
• Findings on context, fallback, and handoff
• A regression pack for the next bot change

Suitable for

Support, sales, and in-app assistants on web, mobile, or voice.

FAQs

Do you test WhatsApp, web chat, and voice the same way?

The conversation logic is shared. The channel adds constraints (message length, buttons, audio). We test the channels you actually ship.

Is this the same as chatbot analytics?

Analytics tell you volume. Testing tells you whether a defined path still works after a change.