BurnRate vs Intencion: Which is Better in 2026?
A comprehensive comparison of BurnRate and Intencion covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose BurnRate if:
- →You want more affordable paid plans (from $12/mo)
- →You need a broader feature set (7 features vs 5)
- →You need per-subagent cost attribution for agents that spawn other agents or coverage across seven ai providers
Choose Intencion if:
- →You need one-line client patch for openai and anthropic in typescript or python or pass/fail verdicts defined in code; goals ranked by failure rate
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BurnRate vs Intencion: At a Glance
Pricing Comparison: BurnRate vs Intencion
Understanding the pricing differences between BurnRate and Intencion is crucial for making the right choice. Here's how their plans compare side by side.
BurnRate Pricing
💡 Pricing takeaway: Both BurnRate and Intencion offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from BurnRate and Intencion stacks up.
What Makes Each Tool Unique
🔵 Unique to BurnRate
Features available in BurnRate but not in Intencion:
- ✓Per-subagent cost attribution for agents that spawn other agents
- ✓Coverage across seven AI providers
- ✓Local-first download rather than a hosted telemetry pipeline
- ✓Nine analytics tabs on Pro, three on Free
- ✓Optimisation engine with more than twenty rules
- ✓Model recommendations and operation-level cost breakdown
- ✓Team-wide cost management on the Team tier
🟣 Unique to Intencion
Features available in Intencion but not in BurnRate:
- ✓One-line client patch for OpenAI and Anthropic in TypeScript or Python
- ✓Pass/fail verdicts defined in code; goals ranked by failure rate
- ✓Run detail marks the exact step that broke, with inputs and outputs
- ✓Unhandled view surfaces requests the agent has no path for at all
- ✓why(run) over MCP so a coding agent can diagnose without the dashboard
Use Case Recommendations
Best for: BurnRate
BurnRate is cost observability for AI coding tools, and its specific insight is subagent visibility. When Claude Code or a similar agent spawns subagents, the spend fragments across processes that no provider dashboard attributes back to the task that caused them — BurnRate surfaces every subagent that gets spawned and tracks per-agent cost across seven providers. That is a genuinely different measurement problem from generic LLM cost tracking, and it is the number engineering managers cannot currently get. The tool is local-first: you download and run it, and the free tier works without a credit card, which matters because the alternative is piping your development telemetry to a third party. The free plan gives a basic analytics dashboard with overview, sessions and costs tabs, support for three providers and 30 days of history — enough to see whether your spend has the shape you assumed. Pro unlocks the full analytics surface of nine tabs plus an optimisation engine with more than twenty rules, model recommendations and operation-level cost breakdown, at a price the company frames against an average saving of $50-plus a month. Team and Enterprise tiers extend to team-wide cost management. Around the product sits a content operation — a 2026 cost report, a five-day email course on cutting AI costs, a blog and an AI spend audit consulting offer — which suggests the company is monetising the expertise as well as the tool.
Ideal use cases:
- •Teams or individuals who need per-subagent cost attribution for agents that spawn other agents
- •Teams or individuals who need coverage across seven ai providers
- •Teams or individuals who need local-first download rather than a hosted telemetry pipeline
- •Teams or individuals who need nine analytics tabs on pro, three on free
- •Anyone focused on cost-tracking workflows
- •Anyone focused on observability workflows
Best for: Intencion
Intencion is observability for AI agents organised around outcomes rather than spans. You patch the client once — a single line wrapping an OpenAI or Anthropic client in TypeScript or Python — and every run is captured with its model, tokens, latency and, critically, a pass-or-fail verdict that you define in code. That verdict is what makes the rest work: runs group by the goal they were serving, goals sort by failure rate, and the biggest problem in the agent sits at the top of the list rather than being buried in a trace viewer. Opening a failing run shows the tool calls in order with inputs, outputs and latency, and the step that broke is marked — a malformed tool call, an ungrounded answer, a step that silently did nothing. The feature that is hardest to find elsewhere is the Unhandled view: requests the agent has no path for at all, ranked by how often users hit them. Those are failures of absence rather than failures of execution, and they double as a build-next list. There is also an MCP surface — a coding agent can call why(run) and get back the failing step, the error and a suggested fix without a human opening the dashboard. Sensitive data is stripped before storage: emails, card numbers, US SSNs and phone numbers never land in the database.
Ideal use cases:
- •Teams or individuals who need one-line client patch for openai and anthropic in typescript or python
- •Teams or individuals who need pass/fail verdicts defined in code; goals ranked by failure rate
- •Teams or individuals who need run detail marks the exact step that broke, with inputs and outputs
- •Teams or individuals who need unhandled view surfaces requests the agent has no path for at all
- •Anyone focused on agent-observability workflows
- •Anyone focused on evals workflows
📊 Other Analytics & BI Tools to Consider
BurnRate and Intencion aren't the only options. Here are other popular tools in the same space:
Amplitude
Product analytics platform with AI insights, funnels & retention analysis for PLG teams
Mixpanel
Event-based product analytics with AI insights and self-serve exploration
Chartsy
Chat-driven MRR, churn, and LTV analytics on top of your Stripe or Paddle data
Fusionaly
Self-hosted, ad-block-proof web analytics in one SQLite file and one Docker container, with a plain-language daily digest and optional natural-language querying via your own key.
Repohistory
Stores GitHub repository traffic past the 14-day retention limit GitHub enforces, with charted long-run analytics, org-wide overview and data export.
Trifle
Time-series product metrics that write into your existing database, with an MCP surface for AI agents
Is one of these your tool?
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Frequently Asked Questions
Is BurnRate better than Intencion?
It depends on your needs. BurnRate offers 7 key features including Per-subagent cost attribution for agents that spawn other agents and Coverage across seven AI providers, while Intencion provides 5 features including One-line client patch for OpenAI and Anthropic in TypeScript or Python and Pass/fail verdicts defined in code; goals ranked by failure rate. BurnRate uses a freemium model with a free tier, while Intencion is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is BurnRate cheaper than Intencion?
BurnRate is cheaper, starting at $12/month compared to Intencion's $90/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use BurnRate and Intencion together?
Yes, many users combine BurnRate and Intencion in their workflow. BurnRate excels at per-subagent cost attribution for agents that spawn other agents, while Intencion shines with one-line client patch for openai and anthropic in typescript or python. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between BurnRate and Intencion?
While both are analytics & bi tools, BurnRate emphasizes per-subagent cost attribution for agents that spawn other agents, whereas Intencion is known for one-line client patch for openai and anthropic in typescript or python. The best choice depends on your specific workflow and feature priorities.
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