Halo vs Proxon (2026)
A side-by-side comparison of Halo and Proxon on pricing, features, and fit, so you can decide which is right for you.
Quick answer
Halo and Proxon are both strong choices, but they fit different needs. Choose Halo if you mainly need debugging unexpected or incorrect llm outputs during development — its edge is completely free and open-source with no usage limits. 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. Halo starts at Free; Proxon starts at On request.
Features compared
- Automatic logging of LLM requests and responses
- Structured observability data for debugging and auditing
- Self-hosted deployment for full data privacy control
- Lightweight integration with existing LLM application pipelines
- 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
- Completely free and open-source with no usage limits
- Self-hosted architecture keeps sensitive prompt data private
- Easy to integrate into existing LLM-based applications
- Lacks a managed cloud option for teams without DevOps resources
- Feature set is minimal compared to commercial LLM observability platforms
- 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
- 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 Halo if
you mainly need to debugging unexpected or incorrect llm outputs during development. Its edge: completely free and open-source with no usage limits.
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 Halo better than Proxon?
Neither is universally better. Halo is stronger for debugging unexpected or incorrect llm outputs during development, with an edge in completely free and open-source with no usage limits. 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, Halo or Proxon?
Halo starts at Free and Proxon starts at On request. Free tier: Halo — Fully free, open-source; Proxon — No public free tier.
What is Halo best for?
Halo is best for debugging unexpected or incorrect llm outputs during development, auditing prompt and response history for compliance or qa purposes, monitoring api latency and usage patterns across llm calls.
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 Halo and Proxon have free plans?
Halo: Fully free, open-source. Proxon: No public free tier. Check each tool's pricing page for current limits, as plans change.