Bottest.ai is an automation tool focused on AI chatbot testing, with the core idea of "Test Smarter Not Harder" and keeping subject matter experts in control during testing. It is positioned as an open-source, no-code automated testing solution suitable for testing various types of AI chatbots.
Purpose
Bottest.ai is mainly used for systematic testing of AI chatbots. It helps teams, before a chatbot goes live or during iteration, discover issues in functionality, performance, and security by recording real conversations, establishing expected baselines, and automatically comparing actual responses with the baselines. The official example shows the results of running a test suite for a refund support scenario, including pass, fail, and mixed statuses, and supports processes such as Human Support Escalation.
Main Capabilities
- No-code automation: No coding required; tests can be recorded and baselines configured through the interface.
- Three-step testing process: Officially described as "record tests, set baselines for conversations, and evaluate responses against established baselines during testing, all in just a few clicks."
- Analytics dashboard: Provides analytics functionality that highlights key areas in the chatbot that need improvement.
- Multi-dimensional evaluation: The officially stated evaluation dimensions include functionality, performance, and security.
- Bring-your-own-infrastructure deployment: Supports deployment on your own infrastructure via Docker, with users having full control.
- Open source and free: The official statement is that Bottest is free and open source.
How to Use
According to the official introduction, the steps for using Bottest include:
- Record Tests: Capture what matters in conversations.
- Set up Baselines: Define expected responses or behavior for conversations.
- Evaluate responses: During testing, actual responses are compared with the baselines and results are generated. In terms of deployment, the official description says it can be deployed on your own infrastructure via Docker in just a few minutes. The official materials do not provide specific installation commands or code examples.
Applicable Scenarios
- Chatbot development teams that want to perform regression testing or quality validation of bots in a no-code way.
- Subject matter experts (such as customer service or business personnel) who want to directlyparticipate in recording test cases and reviewing results.
- Organizations with requirements for data privacy and control that need to deploy testing tools on their own infrastructure.
- Projects that need to evaluate chatbot performance across functionality, performance, and security dimensions.
Limitations
The official materials do not clearly specify details such as the specific chatbot platforms supported, integration methods, concurrent testing capabilities, or supported programming languages or frameworks. Before use, it is recommended to refer to the official documentation for further confirmation.
