Proxon vs role-model

Proxon and role-model are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Proxon

Proxon surfaces AI activity across teams into a single operating record: which tools and agents exist, who owns them, what they cost, and whether they're producing results. The attribution layer connects token spend to specific teams and workflows rather than burying it in an undifferentiated API bill. Adoption tracking lets leadership identify high-performing workflows and push them to teams still running ad hoc. The ceiling appears when you need deep integrations with proprietary internal tooling — the vendor page describes discovery and governance but does not detail connector coverage, so teams with niche or self-built stacks will need to validate fit before committing.

role-model

role-model is an open protocol and reference router runtime that routes LLM requests across endpoints using declared capability profiles, routing policy, and measured performance — then emits a structured decision artifact you can inspect after the fact. The router narrows candidates by role and task metadata, rejects endpoints that fail capability, locality, or budget checks, and scores what's left against latency, cost, and reliability evidence. The decision is deterministic enough to audit, not a hidden runtime guess. The baseline role set covers chat, code editing, code review, tool calling, and embeddings — so it fits mixed-workload deployments out of the box. Teams needing autonomous multi-step planning or tool loops will find this deliberately out of scope.

Attribute	Proxon	role-model
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	Web	Local runtime with operator UI
Pros	Single inventory of all AI tools, agents, and workflows across the organization, so leadership stops discovering production AI systems by accident during an incident or audit. Spend attribution down to the team, workflow, and model level, which means the monthly API bill becomes an actionable breakdown instead of a number nobody can explain. Built-in optimization signals that flag redundant model work and suggest caching or routing changes, so engineering doesn't need a separate cost analysis pass to find waste. Adoption trend tracking by team, which means high-performing workflows can be identified and pushed to underperforming teams rather than staying siloed with whoever built them first. API access for exporting governance and cost data, so Proxon can feed into existing dashboards or alerting pipelines rather than requiring a separate login for every stakeholder.	Explainable RouterDecision artifacts — including the chosen endpoint, fallbacks, exclusions, and named selection reasons — so when a routing call looks wrong, you have evidence to debug rather than a guess to reverse-engineer. Hard eligibility checks across capability, locality, budget, and binding requirements before scoring begins, which means a request that must not leave your network cannot accidentally route to a remote endpoint under load. Scoring uses measured performance evidence first and declared data second, so a local model that has been benchmarked beats a remote model that merely claims low latency — without you having to manually tune weights. Canonical schema definitions for every artifact in the protocol, so swapping a provider or redeploying to a different host doesn't silently change routing behavior or break downstream log parsing. OpenAI-compatible discovery interface for downstream clients, which means existing tooling that already speaks the OpenAI API format can connect without a custom adapter layer.
Cons	The vendor page does not enumerate which AI platforms, model providers, or agent frameworks Proxon connects to natively. Teams running self-built or niche tooling will find gaps in the discovery layer — activity that runs outside supported connectors stays invisible, which defeats the core premise of a complete inventory. No self-hosted deployment option is described. Organizations in regulated sectors where activity metadata cannot leave their own infrastructure hit a hard architectural wall here, and at that point the evaluation moves to purpose-built on-premises governance tools regardless of what Proxon offers. Policy enforcement and approval flows are listed as capabilities but the vendor page does not show the depth of the rules engine. Teams that need granular, conditional access controls — for example, blocking specific models for specific data classifications — will need to pressure-test whether Proxon's governance layer goes deep enough or whether they need a dedicated AI access control product alongside it.	role-model has no agent loop — it routes a request to an endpoint, it does not decide what the next request should be. Teams building systems where the model output determines the next action will need a separate orchestration layer, and the boundary between the two systems requires explicit wiring and maintenance. The baseline role taxonomy covers the documented set of general chat, code editing, code review, tool calling, and embeddings — workloads that fall outside those role IDs require teams to define custom role and capability profiles against the protocol spec, which adds schema work before the router is useful. There is no managed cloud runtime. The packaged reference runtime runs self-hosted, which means infrastructure ownership, upgrade management, and observability pipeline setup land on the team deploying it. Teams that hit operational overhead they didn't budget for tend to move toward a hosted LLM gateway product with a UI instead.

Bottom line

Proxon is paid while role-model is free; role-model is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Proxon and role-model?

Proxon is Paid, while role-model is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Proxon better than role-model?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.