Agent Analytics Platform

Kubit is an agent analytics platform that bridges product analytics and LLM observability.

Reviewed by 7wData

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Publisher review

Kubit is an agent analytics platform that bridges product analytics and LLM observability. It maps user behavior, intent, and sentiment directly to LLM traces, giving developers the full context to debug and optimize AI agents. The platform is built for AI product engineers who need to understand why users are frustrated, not just what broke. It integrates with major LLM observability tools like Langfuse, Braintrust, LangSmith, and Arize, as well as AI frameworks such as Langchain and Vercel, with native OpenTelemetry support. Kubit also supports coding agents via plugins for Claude Code and Cursor, enabling auto-fixes without leaving the editor.

Kubit enriches 100% of traces with zero sampling, using conversation intelligence to extract intent, sentiment, and resolution from raw JSON logs. It correlates clickstream events, LLM traces, tool calls, prompt versions, and user intent in one place, eliminating the need to manually stitch data across six different tools. The platform offers product analytics for LLM observability, allowing teams to track token costs and error rates by intent and friction signals, explore escalation funnels, and follow user retention by cohort before and after agent interactions. Kubit provides self-service analytics to discover patterns at scale, going beyond simple performance monitoring and error tracking.

Kubit competes with Houseware, Viable Fit, Successeve, and Tribyl. It differentiates itself by focusing on the intersection of user behavior and LLM reasoning, rather than just app market intelligence or mobile attribution. Unlike Data.ai, which excels at competitive app intelligence but lacks paid media integrations and cross-channel attribution, Kubit is designed for AI agents and provides actionable context directly into coding workflows. The platform has a 100% positive business outlook on Glassdoor, with high ratings for senior management (4.9), culture and values (4.3), and career opportunities (4.2).

Honest trade-offs: Kubit is a fully remote company, which may not suit everyone. The fast-paced startup environment can be demanding, with employees reporting being busy most of the time. The platform is still relatively new and may lack the extensive integration ecosystem of more established observability tools. Pricing scales with trace volume, which could become costly for high-volume deployments beyond the included monthly traces. Additionally, the platform's focus on AI agents means it may not be suitable for teams building traditional software or mobile apps without LLM components.

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How it works

  1. User behavior mapping

    Maps user behavior, intent, and sentiment directly to LLM traces for full context in debugging and optimizing AI agents.

  2. Zero-sampling enrichment

    Enriches 100% of traces with zero sampling, using conversation intelligence to extract intent, sentiment, and resolution.

  3. LLM observability integration

    Integrates with Langfuse, Braintrust, LangSmith, Arize, Langchain, and Vercel, with native OpenTelemetry support.

  4. Product analytics for LLM

    Offers self-service analytics to track token costs, error rates, escalation funnels, and user retention by cohort.

  5. Coding agent plugins

    Supports Claude Code and Cursor via MCP, allowing coding agents to trigger auto-fixes without opening a browser.

  6. Conversation intelligence

    Extracts intent, sentiment, and resolution from traces to understand root causes of user frustration.

  7. Total visibility

    Correlates clickstream events, LLM traces, tool calls, prompt versions, and user intent in one unified view.

Strengths and trade-offs

Strengths

  • Kubit enriches 100% of traces with zero sampling, unlike expensive LLM-as-a-Judge or BYOM approaches.
  • The platform has a 4.4 Glassdoor rating with 100% positive business outlook and a 4.9 score for senior management.
  • It integrates with major LLM observability tools including Langfuse, Braintrust, LangSmith, Arize, Langchain, and Vercel.
  • Pricing starts at $0 for the Developer plan with 100,000 traces/month, and a 30-day free trial requires no credit card.

Trade-offs

  • Kubit is a fully remote company, which may not suit employees who prefer in-person collaboration.
  • The fast-paced startup environment can be demanding, with employees reporting being busy most of the time.
  • Usage-based pricing of $0.0003 per trace can become costly for high-volume deployments beyond included monthly traces.
  • The platform's focus on AI agents means it may not be suitable for teams building traditional software or mobile apps without LLM components.

Pricing context

Free 30-day trial. Developer: $0/month (100,000 traces, 45-day data access, 1 seat). Growth: $199/month (1,000,000 traces, 200-day data access, 20 seats, Product Analytics add-on).

Enterprise: custom pricing (10,000,000 traces, unlimited data access, unlimited seats, dedicated solution architect, SSO, warehouse-native option, SLA). Usage billing: $0.0003/trace.

Getting started with Agent Analytics Platform

  1. Sign up for a free trial

    Go to the Kubit website and click the Get Started button. Enter your email and create a password. No credit card is required for the 30-day free trial, which includes 100,000 traces.

  2. Connect your LLM observability tool

    In the Kubit dashboard, navigate to Integrations and select your LLM observability tool, such as Langfuse, Braintrust, or LangSmith. Follow the prompts to authorize the connection and start ingesting traces.

  3. Configure conversation intelligence

    Enable zero-sampling enrichment in the settings to extract intent, sentiment, and resolution from all traces. This ensures every user interaction is analyzed without missing any data.

  4. Explore user behavior and traces

    Open the unified view to correlate clickstream events, LLM traces, tool calls, and user intent. Use the self-service analytics to filter by intent or friction signals and identify patterns in user frustration.

  5. Set up coding agent plugins

    Install the Kubit plugin for Claude Code or Cursor via MCP. Configure the plugin to trigger auto-fixes based on trace insights, allowing you to debug and optimize directly from your editor.

Frequently Asked Questions

What is an agent analytics platform and how does it help debug AI agents?

An agent analytics platform like Kubit bridges product analytics and LLM observability. It maps user behavior, intent, and sentiment directly to LLM traces, giving developers full context to debug and optimize AI agents by understanding why users are frustrated.

How does Kubit enrich LLM traces without sampling?

Kubit enriches 100% of traces with zero sampling using conversation intelligence. It extracts intent, sentiment, and resolution from raw JSON logs, providing complete visibility into every user interaction without missing data points.

Which LLM observability tools does Kubit integrate with?

Kubit integrates with major LLM observability tools including Langfuse, Braintrust, LangSmith, and Arize, as well as AI frameworks like Langchain and Vercel. It also supports native OpenTelemetry for seamless data collection.

What product analytics features does Kubit offer for AI agents?

Kubit provides self-service analytics to track token costs, error rates, escalation funnels, and user retention by cohort. It correlates clickstream events, LLM traces, tool calls, and prompt versions in one unified view for pattern discovery.

How much does Kubit cost and what are the pricing plans?

Kubit offers a free 30-day trial. The Developer plan is $0/month for 100,000 traces, 45-day data access, and 1 seat. Growth is $199/month for 1,000,000 traces. Enterprise has custom pricing with 10,000,000 traces and unlimited data access.

What are the limitations of using Kubit for AI agent analytics?

Kubit is fully remote and fast-paced, which may not suit everyone. Pricing scales with trace volume at $0.0003 per trace, potentially costly for high-volume use. It focuses on AI agents, so it may not fit traditional software or mobile apps without LLM components.

Alternatives

How Agent Analytics Platform compares

Direct head-to-head against 3 competitors. Picked by 7wData.

This tool

Agent Analytics Platform

Pricing
Free 30-day trial. Developer: $0/month (100,000 traces, 45-day data access, 1 seat). Growth: $199/month (1,000,000 traces, 200-day data access, 20 seats, Product Analytics add-on). Enterprise: custom pricing (10,000,000 traces, unlimited data access, unlimited seats, dedicated solution architect, SSO, warehouse-native option, SLA). Usage billing: $0.0003/trace.
Target
Kubit is an agent analytics platform that bridges product analytics and LLM observability.
Strength
Kubit enriches 100% of traces with zero sampling, unlike expensive LLM-as-a-Judge or BYOM approaches.
Watch for
Kubit is a fully remote company, which may not suit employees who prefer in-person collaboration.

Sigma

Pricing
$30/user/month
Target
Business analysts
Deployment
Cloud
Strength
Spreadsheet-like UI
Watch for
Limited advanced analytics

Qlik Cloud Analytics

Pricing
$20/user/month
Target
Visual analysts
Deployment
SaaS
Strength
Associative engine
Watch for
Steep learning curve

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Sources

Reporting on this tool draws on these publicly available sources.

  1. kubit.ai
  2. kubit.ai
  3. www.glassdoor.com
  4. www.capterra.com
  5. www.cbinsights.com