Memori vs Proxon (2026)
A side-by-side comparison of Memori and Proxon on pricing, features, and fit, so you can decide which is right for you.
Quick answer
Memori and Proxon are both strong choices, but they fit different needs. Choose Memori if you mainly need maintaining context across multi-session autonomous ai agent workflows — its edge is captures richer context from agent traces rather than simple chat logs. 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. Memori starts at $20/month based on usage and scale; Proxon starts at On request.
Features compared
- Agent trace-based persistent memory extraction
- Cross-session memory storage for LLM agents
- Structured memory retrieval for autonomous workflows
- Developer API for integrating memory into existing agent 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
- Captures richer context from agent traces rather than simple chat logs
- Reduces engineering effort needed to build custom memory layers
- Improves agent performance and decision quality over multiple sessions
- Limited public documentation may make initial setup challenging for new users
- Primarily built for developers, making it less accessible to 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 Memori if
you mainly need to maintaining context across multi-session autonomous ai agent workflows. Its edge: captures richer context from agent traces rather than simple chat logs.
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 Memori better than Proxon?
Neither is universally better. Memori is stronger for maintaining context across multi-session autonomous ai agent workflows, with an edge in captures richer context from agent traces rather than simple chat logs. 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, Memori or Proxon?
Memori starts at $20/month based on usage and scale and Proxon starts at On request. Free tier: Memori — Free tier available with limited memory storage and trace ingestion; Proxon — No public free tier.
What is Memori best for?
Memori is best for maintaining context across multi-session autonomous ai agent workflows, improving consistency in llm-powered task automation pipelines, reducing repeated errors by grounding agents in historical trace memory.
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 Memori and Proxon have free plans?
Memori: Free tier available with limited memory storage and trace ingestion. Proxon: No public free tier. Check each tool's pricing page for current limits, as plans change.