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TokenPath vs Curbi

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

TokenPath compared with Curbi
DetailTokenPath logo TokenPathCurbi logo Curbi
What it doesCitations, built for AI agents Check AI agent replies against configured rules and verify signed records
StageNot given Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelFreemium Freemium
PricingFree tier for small requests with no API key required; 10 million free tokens to start; $1 per million tokens for pay-as-you-go, with discounts available at volume or with annual commitments; failed requests are never charged. Free: local open-source checker, browser policy checks, six read-only MCP tools, regression export and offline verification. Managed Check API: $1 per 1,000 checked replies, USD, monthly usage billing through Stripe.
Key features
  • Token-level attribution with confidence scores
  • Works with any AI model without access to weights or internals
  • Processes documents up to 1 million tokens
  • Returns results in under 2 seconds for 20,000-token documents
  • On-premise and air-gapped deployment options
  • PDF support with character-level mapping
  • Supports 23+ languages including Indian languages
  • Chrome browser extension for page and PDF tracing
  • Raw token-by-token heatmaps available via API
  • No data logging or training on request content
  • Check agent replies against configured pricing, forbidden phrases, and action records
  • Policy Check tool with browser interface for testing rules
  • Model Context Protocol endpoint for Claude, ChatGPT and other MCP clients
  • Offline verification with signed records and Merkle proofs
  • Repair Lab for reproducing and fixing integration failures
  • Managed Check API with pricing transparency
  • MIT-licensed open-source local checker
  • Framework connectors for LangChain and Vercel AI SDK
  • MCP Chaos proxy for testing agent behavior
What makes it different
  • Measures attention directly from the model's computation rather than asking the model to cite itself, providing verifiable attribution
  • Achieves frontier-grade citation quality at 7x lower cost and 5-6x faster than alternatives
  • Never confused by duplicate facts—identifies the exact occurrence the answer used even when values appear multiple times
  • Lands on exact tokens down to character level, not just document chunks
  • Works on any model's output post-generation without modifying inference pipeline
  • Verifiable AI agent compliance without authorization or permission granting
  • Evidence and records portable across platforms and models
  • Transparent per-reply pricing with clear usage examples
  • Open-source core with portable verification
Community votes00
DR (Domain Rating by Ahrefs)2 no change since last checkNot checked yet no change since last check
Trust Flow (Majestic)30
Citation Flow (Majestic)160
Referring domains (Majestic)360

5 details filled in for both companies.

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