Kubit

What is Kubit?

Kubit is a product analytics and observability tool for teams building AI agents and AI-powered product experiences. It connects agent traces, prompts, tool calls, latency, and token usage with user events such as re-prompts, rage clicks, drop-offs, retention, and conversion. Product engineers can use those joined insights to understand whether an agent failure is a model issue, UX issue, performance issue, or funnel issue. Kubit supports OTel, CDP data, and warehouse-native setups so teams can analyze behavior without moving sensitive data unnecessarily.

How to use Kubit?

1. Connect Kubit to agent traces through OpenTelemetry or another supported source.
2. Link user behavior data from a CDP, event pipeline, or data warehouse.
3. Map prompts, tool calls, and agent sessions to user outcomes and funnel steps.
4. Analyze re-prompts, drop-offs, latency, token usage, and conversion impact together.
5. Feed the findings into engineering or coding-agent workflows to debug and improve the product.

Core Features

• Agent-user analytics - Joins AI traces with product behavior and outcomes.
• OpenTelemetry support - Ingests agent spans through open standards.
• Warehouse-native option - Keeps sensitive user data in the customer data warehouse.
• User-agent funnels - Shows where agent behavior affects conversion, retention, and drop-off.
• Behavioral debugging context - Gives engineering teams concrete signals to fix agent UX issues.
• MCP and coding-agent workflow - Provides analytics context that agents can use for verification loops.

Use Cases

• AI product debugging - Find why users keep re-prompting or abandoning an agent workflow.
• Agent funnel analysis - Measure how tool calls, latency, or hallucinations affect conversion.
• Warehouse-native analytics - Analyze agent behavior without copying sensitive data into another silo.
• Product iteration - Give engineers evidence-backed issues to fix in AI product loops.