# Proxon

> Proxon is the management layer for your AI workforce. It discovers every AI tool, agent, and workflow running across a company, assigns each one an owner and a policy, attributes AI spend to teams and outcomes, and propagates the workflows that work best.

Proxon turns scattered AI adoption into one managed operating system: discovery, ownership, cost attribution, policy enforcement, and the propagation of high-performing patterns. Built for Heads of AI, CIOs/CTOs, CISOs, legal, finance, and operations leaders.

## Product

- [Proxon — The management layer for your AI workforce](https://proxon.ai/): Turn AI from scattered experiments into a managed system for discovery, ownership, spend, policy, and growth.
- [Product demo](https://proxon.ai/demo): Walk the full operating surface: adoption, org overview, agents and skills, inventory, outcomes, cost intelligence, and compliance.
- [Pricing](https://proxon.ai/pricing): Plans and pricing for the Proxon AI management platform.
- [Cost Intelligence](https://proxon.ai/cost): Attribute AI spend to vendors, models, teams, workflows, and business outcomes.
- [Compliance & Control](https://proxon.ai/compliance): Map AI data flows, enforce policies at execution time, and keep full audit trails.
- [Knowledge Transfer](https://proxon.ai/knowledge): Extract high-performing AI workflows and propagate them across similar teams.
- [AI Skill Levels](https://proxon.ai/levels): Explore the six levels of AI work, from safe first use to recursive improvement systems.
- [Ownership & Accountability](https://proxon.ai/own): Give every AI agent, workflow, and output an owner, a purpose, and a lineage trail.
- [AI Readiness](https://proxon.ai/compete): Benchmark AI readiness and build a deployment roadmap across every function.
- [Whitepaper](https://proxon.ai/whitepaper): The full Proxon thesis: AI workforce management, cost, governance, and propagation.
- [Blog](https://proxon.ai/blog): Research and analysis on AI governance, cost, ownership, and adoption.

## Industries

- [AI Management for Financial Services](https://proxon.ai/ft): Manage observed and registered AI systems, attributable adoption where identity is available, registered workflows, and available spend context across your financial institution.
- [AI Management for Software, Cloud, and Developer Tools](https://proxon.ai/sw): Manage observed and registered AI systems, attributable adoption, registered workflows, and captured or provider-reported spend across software delivery.
- [AI Management for Professional Services and BPO](https://proxon.ai/ps): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across client delivery and business-process operations.
- [AI Management for Healthcare and Life Sciences](https://proxon.ai/hls): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across healthcare administration and life-sciences work.
- [AI Management for Retail and Ecommerce](https://proxon.ai/ret): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across retail and ecommerce teams.
- [AI Management for Real Estate and Construction](https://proxon.ai/re): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across real-estate and construction organizations.
- [AI Management for Media and Telecommunications](https://proxon.ai/mt): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across media and telecommunications organizations.
- [AI Management for Energy and Natural Resources](https://proxon.ai/enr): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across energy and natural-resources organizations.
- [AI Management for HR and Workforce Teams](https://proxon.ai/hr): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across HR and workforce operations.
- [AI Management for Manufacturing and Industrial Companies](https://proxon.ai/mfg): Manage observed and registered AI systems, attributable adoption, registered workflows, and available spend context across manufacturing and industrial organizations.

## Guides

- [AI Usage Visibility Guide](https://proxon.ai/guide/ai-usage-visibility): How to see every AI tool, agent, and workflow running across an organization.
- [Shadow AI Discovery Guide](https://proxon.ai/guide/shadow-ai-discovery): How to find unapproved AI tools, agents, and data flows before they become incidents.
- [AI Governance Guide](https://proxon.ai/guide/ai-governance): How to apply ownership, policy, and audit controls to the AI systems a company runs.
- [AI Cost Intelligence Guide](https://proxon.ai/guide/ai-cost-intelligence): How to attribute AI spend to teams, workflows, and outcomes instead of invoices alone.
- [AI Adoption Measurement Guide](https://proxon.ai/guide/ai-adoption-measurement): How to measure who is getting better at AI across people, teams, and departments.
- [AI Policy Automation Guide](https://proxon.ai/guide/ai-policy-automation): How to turn AI policy documents into execution-time rules that actually enforce.
- [AI Vendor Inventory Guide](https://proxon.ai/guide/ai-vendor-inventory): How to maintain one inventory of AI models, tools, MCP servers, and data sources.
- [AI ROI Reporting Guide](https://proxon.ai/guide/ai-roi-reporting): How to connect AI usage to business metrics and report attributable gains.

## Resources

- [AI data collection: how Proxon sees your AI usage — Proxon](https://proxon.ai/data-collection): Every data collection method Proxon offers, what each one sees, and how to choose between them.
- [Proxon on your computer: what it can and can't see](https://proxon.ai/observers): What each observer running on an employee machine can and cannot see, in plain language.

## Documentation

- [Proxon Docs](https://proxon.ai/docs): Product documentation: collection methods, capture levels, observers, and the OpenTelemetry and Agent Observer integrations.

## Company

- [About](https://proxon.ai/about): What Proxon is and why AI needs a management layer.
- [Security](https://proxon.ai/security): How Proxon secures customer data and the AI systems it governs.
- [Careers](https://proxon.ai/careers): Open roles at Proxon.
- [Contact](https://proxon.ai/contact): Get in touch with the Proxon team or book a demo.

_Last updated: 2026-09-08. Full index: https://proxon.ai/llms-full.txt · Sitemap: https://proxon.ai/sitemap.xml_