Otari vs Proxon (2026)
A side-by-side comparison of Otari and Proxon on pricing, features, and fit, so you can decide which is right for you.
Quick answer
Otari and Proxon are both strong choices, but they fit different needs. Choose Otari if you mainly need building multi-model llm pipelines for production applications — its edge is completely free and open-source with no usage fees. 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. Otari starts at Free; Proxon starts at On request.
Features compared
- Open-source LLM routing and workload management
- Self-hostable with no vendor lock-in
- GitHub-native project for easy forking and contribution
- Mozilla AI-backed responsible AI development principles
- 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 fees
- Backed by Mozilla AI, ensuring a focus on transparency and safety
- Full customizability and extensibility via GitHub
- Requires developer expertise to set up and configure
- Lacks a managed cloud option or GUI for non-technical users
- 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 Otari if
you mainly need to building multi-model llm pipelines for production applications. Its edge: completely free and open-source with no usage fees.
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 Otari better than Proxon?
Neither is universally better. Otari is stronger for building multi-model llm pipelines for production applications, with an edge in completely free and open-source with no usage fees. 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, Otari or Proxon?
Otari starts at Free and Proxon starts at On request. Free tier: Otari — Fully free and open-source; Proxon — No public free tier.
What is Otari best for?
Otari is best for building multi-model llm pipelines for production applications, experimenting with intelligent routing strategies across different language models, self-hosting ai middleware as an alternative to proprietary platforms.
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 Otari and Proxon have free plans?
Otari: Fully free and open-source. Proxon: No public free tier. Check each tool's pricing page for current limits, as plans change.