Traditional analytics tools like Google Analytics or Adobe Analytics require developers to manually define event schemas and instrument applications to trigger those events at specific points in the user journey. This approach works well for conventional web and mobile applications where the user experience is structured and predictable.
However, AI applications present a new challenge. Human–AI interactions are unstructured, dynamic, and often non-linear—making it nearly impossible to predefine event schemas in advance. Maintaining such schemas as the AI evolves not only becomes unmanageable but also drains valuable time from your product managers, architects, and data analysts.
Mindlytics solves this problem with its built-in AI-powered analytics engine. It automatically interprets human–AI interactions and generates meaningful analytics events in real time, using intuitive and consistent naming conventions. This eliminates the need for manual instrumentation and schema maintenance—freeing your teams to focus on innovation, not plumbing.
For hybrid applications, Mindlytics also supports custom events with user-defined schemas. This allows developers to combine insights from AI-driven conversations with traditional UI-based user journeys—creating a unified view of engagement across both structured and unstructured experiences.
- Integrate Mindlytics via SDK or API into your AI app or agent.
- Capture raw conversations or [Human-AI] interactions in real time. Instrument the SDK to pipe user prompts and AI responses to mindlytics analytics engine.
- Process interactions using AI-powered mindlytics analytics engine to decode user intent and agent performance. Let mindlytics process interactions to auto generate analytics events. (optionally add custom events as required.)
- Visualize & Analyze [Human-AI] engagement metrics through interactive dashboards that highlight intent fulfillment, friction hotspots, sentiment, funnels, and more.