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Prefactor vs Proxon (2026)

A side-by-side comparison of Prefactor and Proxon on pricing, features, and fit, so you can decide which is right for you.

Last updated: July 30, 2026

Quick answer

Prefactor and Proxon are both strong choices, but they fit different needs. Choose Prefactor if you mainly need engineering teams deploying production ai agents that handle sensitive user data or financial operations — its edge is blocks risky agent actions in real time rather than simply logging them after the fact. Choose Proxon if you need auditing all ai applications in use across a large enterprise to identify shadow it risks — its edge is provides comprehensive visibility into both approved and unauthorized ai tool usage. Prefactor starts at Contact for pricing; Proxon starts at On request.

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Prefactor logo
Prefactor

Stop risky AI agent actions before they reach production users.

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Proxon logo
Proxon

Full visibility and control over every AI tool in your organization.

PricingFreemium
PricingPaid
Starts atContact for pricing
Starts atOn request
Free tier25,000 spans/month, no credit card required
Free tierNo public free tier
RatingNot yet rated
RatingNot yet rated
Best forEngineering teams deploying production AI agents that handle sensitive user data or financial operations
Best forAuditing all AI applications in use across a large enterprise to identify shadow IT risks
Key strengthBlocks risky agent actions in real time rather than simply logging them after the fact
Key strengthProvides comprehensive visibility into both approved and unauthorized AI tool usage
Main drawbackPaid tier pricing is not publicly listed, making budget planning difficult without contacting sales
Main drawbackPricing is not publicly available, making it difficult to budget without a sales conversation

Features compared

Prefactor

  • Real-time agent run scoring for quality, drift, and risk using LLM-as-judge and technical evaluations
  • Runtime enforcement that can pause or block high-risk actions like PII exposure or financial transactions before execution
  • Native TypeScript and Python SDKs with support for LangChain, Claude, Vercel AI, OpenClaw, and LiveKit
  • Human-in-the-loop approval workflows for sensitive agent actions alongside automatic blocking for the highest-risk scenarios

Proxon

  • Automated discovery and inventory of all AI tools across an organization, including shadow AI
  • Ownership assignment and policy binding per AI system
  • Real-time spend tracking and budget attribution for each AI tool
  • Centralized compliance and governance dashboard for IT and security teams

Pros & cons

Prefactor

Pros

  • Blocks risky agent actions in real time rather than simply logging them after the fact
  • Generous free tier of 25,000 spans per month with no credit card required
  • Broad framework compatibility through native SDKs covers most major agent development stacks

Cons

  • Paid tier pricing is not publicly listed, making budget planning difficult without contacting sales
  • SOC 2 Type II certification is still in progress, which may be a blocker for some enterprise procurement teams

Proxon

Pros

  • Provides comprehensive visibility into both approved and unauthorized AI tool usage
  • Directly links AI tools to owners, policies, and costs for clear accountability
  • Designed specifically for enterprise security and IT governance workflows

Cons

  • Pricing is not publicly available, making it difficult to budget without a sales conversation
  • May require significant onboarding effort to fully integrate with existing IT infrastructure

The verdict

Choose Prefactor if

you mainly need to engineering teams deploying production ai agents that handle sensitive user data or financial operations. Its edge: blocks risky agent actions in real time rather than simply logging them after the fact.

Choose Proxon if

you mainly need to auditing all ai applications in use across a large enterprise to identify shadow it risks. Its edge: provides comprehensive visibility into both approved and unauthorized ai tool usage.

Frequently asked questions

Is Prefactor better than Proxon?

Neither is universally better. Prefactor is stronger for engineering teams deploying production ai agents that handle sensitive user data or financial operations, with an edge in blocks risky agent actions in real time rather than simply logging them after the fact. Proxon is stronger for auditing all ai applications in use across a large enterprise to identify shadow it risks, with an edge in provides comprehensive visibility into both approved and unauthorized ai tool usage. Pick based on your main task.

Which is cheaper, Prefactor or Proxon?

Prefactor starts at Contact for pricing and Proxon starts at On request. Free tier: Prefactor — 25,000 spans/month, no credit card required; Proxon — No public free tier.

What is Prefactor best for?

Prefactor is best for engineering teams deploying production ai agents that handle sensitive user data or financial operations, companies that need compliance-grade oversight of autonomous agent behavior without halting development velocity, developers building on popular agent frameworks who want enforcement guardrails without rebuilding their agent architecture.

What is Proxon best for?

Proxon is best for auditing all ai applications in use across a large enterprise to identify shadow it risks, enforcing ai usage policies and mapping each tool to a responsible owner, tracking and controlling ai-related software spend across business units.

Do Prefactor and Proxon have free plans?

Prefactor: 25,000 spans/month, no credit card required. Proxon: No public free tier. Check each tool's pricing page for current limits, as plans change.