DRUID AI, a provider of conversational and agentic artificial intelligence, today unveiled DRUID QA Agent, which automates quality assurances (QA) and enables companies to test the accuracy of their AI agents prior to launch.
By integrating with any type of large language model (LLM) or AI copilot, the solution streamlines the launch of autonomous AI agents. It's a virtual testing department that tests DRUID AI implementations and other vendors' AI solutions. Customers can select and optimize the best solution for their specific needs by testing as different personas in a centralized platform to identify risks and solutions, improve performance, and significantly reduce testing time.
DRUID QA Agent allows companies to do the following:
- Accelerate AI project launches with an 80 percent reduction in testing time;
- Test real-world use cases and AI-generated scenarios;
- Get virtual assistants up to 95 percent accuracy;
- Test cases based on knowledgebase content, previously recorded conversations (including voice recordings from the contact center), hypothetical conversations, and user profiles connected with business records;
- Automatically run potential conversations and verify the results for accuracy;
- Get analytics on the impact of tuning changes on answer or transaction accuracy;
- A/B test and regression test comparisons between the performance of different LLM models, different versions, and different parameters; and
- Test the performance of different AI agents, such as Microsoft Copilot, Salesforce Einstein, Servicenow agents, etc.
The solution comes with full enterprise data security, data privacy, and governance. It is available for cloud, on-premise, or hybrid deployment.
"Agentic AI is quickly revolutionizing the speed and accuracy with which companies can communicate with their stakeholders," said Liviu Dragan, co-founder and CEO of DRUID AI, in a statement. "Whether organizations are looking to implement autonomous AI agents internally or externally, our QA Agent equips enterprises with the confidence and peace of mind needed to embrace AI, using rigorous validation and ensuring a smooth deployment and optimal performance from day one."