Enrich traces with intent and sentiment
Combine prompts, tool calls, model output, and surrounding context so traces include the behavioral signals needed to explain what happened.
Kubit
Kubit is a product analytics and observability platform for AI agents that connects traces to user behavior. It helps teams understand why users re-prompt, drop off, or convert, and feed those insights back into AI workflows.
What Kubit is
Kubit is a product analytics and observability platform for AI applications and agents. It is designed to connect agent traces with user behavior so teams can see why users re-prompt, drop off, or convert.
The homepage positions the product as a way to bridge a gap between traditional observability, which shows system behavior, and product analytics, which shows user actions. Kubit combines both sides so teams can investigate outcomes, then feed those findings back into coding agents and AI workflows.
Core capabilities
Tie performance to outcomes
Connect infrastructure signals such as latency and token usage to product outcomes like DAU and retention.
Track user-agent funnels
Analyze where hallucinations, bad tool calls, or other failures disrupt the path from first interaction to conversion.
Map AI journeys
Follow re-prompts, rage clicks, intent, and sentiment to identify UX dead ends that are hard to spot in observability tools alone.
Build granular cohorts
Create segments that combine agent interactions and user behavior across multiple conditions.
Use open data pathways
Move data through open standards, with OTel, CDP, SQL, and warehouse-native workflows instead of a proprietary pipeline.
Practical use cases
Debug repeated re-prompts
Use Kubit to investigate why users re-prompt an agent, then trace the issue back to prompts, tool calls, or model output that may have confused the workflow.
Analyze drop-off in agent journeys
Track where users abandon an AI flow and correlate the exit point with latency, hallucinations, or broken tool calls to find the step that needs attention.
Connect technical metrics to business impact
Measure whether a model or infrastructure change affects product outcomes by correlating latency, token use, DAU, and retention.
Segment users across AI and product events
Build cohorts that combine agent behavior and user actions so product or data teams can compare segments by release, platform, campaign, or behavior pattern.
Pros and Cons
Pros
- Connects agent traces to user behavior instead of treating observability and product analytics separately.
- Supports open standards and warehouse-native workflows, including OTel, CDP, SQL, and Bring Your Own Warehouse on higher tiers.
- Includes behavioral analysis features such as funnels, journeys, cohorts, and outcome correlation.
- Shows multiple pricing entry points, including a free Starter plan, a paid Pro plan, and Enterprise sales contact flow.
- Positions the product for both analysts and coding-agent workflows, including MCP-oriented usage.
Cons
- The source does not include detailed documentation on setup steps, limits, or advanced configuration.
- Several integration and workflow details are mentioned only at a high level, so some capabilities are not fully specified on the source pages.
- Pricing is usage-based and plan details are partly summarized rather than fully enumerated in the provided content.
FAQ
What does Kubit do?
Kubit is a product analytics and observability platform for AI features and agents. It connects agent traces with user behavior so teams can investigate re-prompts, drop-offs, conversions, and other outcomes in one place.
What pricing options does Kubit offer?
The pricing page lists Starter, Pro, and Enterprise plans. Starter is free with usage-based pricing, Pro is $199/month plus usage-based pricing, and Enterprise uses custom terms with dedicated support.
What integrations or data sources does Kubit support?
The homepage says Kubit supports open standards such as OTel, CDP, SQL, and a warehouse-native workflow. The pricing page also mentions OTel and CDP integration, plus a Bring Your Own Warehouse option on higher tiers.
Do I need to install a specific SDK?
Kubit says you can ingest agent traces via OTel, pull clickstream events from your CDP, or query your warehouse directly. It also says you can use an OTel bridge for Sentry and Embrace.
Which coding-agent workflows does Kubit support?
The homepage says Kubit feeds behavioral insights into coding agents and mentions Claude Code, Cursor Skills, and MCP-based workflows. The pricing page also lists an Ask Kubit experience and MCP Server among the included features.
Quick Facts
- Category
- Product analytics and observability for AI agents
- Website
- kubit.ai
- Primary workflow
- Connect agent traces to user behavior and outcomes
- Data model
- Open standards and warehouse-native
- Pricing model
- Starter free, Pro paid, Enterprise custom
- Notable integrations
- OTel, CDP, SQL, warehouse, MCP
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