Question: How can I evaluate the quality of conversations between users and my AI system before deploying it?

If you want to gauge the quality of conversations between users and your AI system, Align AI is a useful platform for doing so. It offers real-time data analysis, user behavior insights and auto-generated action items to fine-tune your AI chatbots. The platform can be used in the cloud or on-premise, so it should work in many industries and use cases, and it complies with industry standards like SOC 2 and GDPR for data protection.

Another good choice is LangWatch, which can help you ensure the quality and safety of your generative AI products. It offers real-time metrics for conversion rates, output quality and user feedback, and can help you avoid problems like jailbreaking and sensitive data exposure. LangWatch is geared for developers and product managers who need to ensure their AI products perform well and don't cause problems.

If you want a more meeting-centric approach, Avoma offers AI Meeting Assistant that transcribes, summarizes and analyzes meetings to help you manage them. It handles the meeting lifecycle, which makes it useful for remote teams, and it can help you collaborate with others with features like AI-generated notes and conversation intelligence. The tool can help you make data-driven decisions and get more out of your meetings.

Spoke is another general-purpose tool that offers a pay-as-you-go API for meeting bots. It gives you access to transcripts, video recordings and meeting metadata, as well as features like live assistance, data extraction and custom information extraction. Spoke supports multiple languages and can link to CRM systems, so it's a good option for teams that want to get more out of meetings and automate their CRM updates.