Proxon vs Tenure

Proxon and Tenure 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.

Tenure

Where most memory systems rely on similarity search with soft boundaries, Tenure enforces hard scope isolation at the structural level: engineering beliefs stay in engineering sessions, Project A never bleeds into Project B. The vendor's benchmark claims a drift score of 0.00 against competing memory systems that score above 0.80. Retrieval latency is documented at 15ms with 1.0 precision. The self-hosted Helm install takes roughly 30 seconds and exposes an OpenAI-compatible endpoint, so existing clients require no code changes. The ceiling appears when your team needs managed infrastructure or enterprise support — neither is documented on the vendor site.

Attribute	Proxon	Tenure
Pricing	Paid	Paid
Free trial	No	No
Open source	No	No
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	Web	VS Code, VSCodium, OpenAI-compatible clients, Open WebUI, Kubernetes, Docker, Linux/macOS/Windows
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.	Hard structural scope isolation between projects and teams, so Customer A's session beliefs cannot surface in Customer B's responses — the failure mode that probabilistic filters cannot fully prevent. Belief versioning with supersession, which means retired decisions are archived rather than deleted, giving you a full decision history for compliance audits without polluting active retrieval. OpenAI-compatible `/v1` endpoint, so VS Code, Open WebUI, and other OpenAI-client tools connect without code changes — reducing the integration cost that typically blocks memory layer adoption. No call-home telemetry and a self-hosted deployment model, which means memory data never transits a third-party API — a hard requirement for teams under data residency or regulatory constraints. Real-time audit trail recording identity, timestamp, and the triggering query at write time rather than reconstructed post-hoc, so the record holds up under compliance review.
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.	The Helm chart deployment requires a running Kubernetes cluster; teams without that infrastructure hit a dead end before they can evaluate the memory layer itself, and the vendor documents no alternative managed hosting path. Scope isolation is a structural guarantee only within Tenure's own belief store — if your agent pipeline mixes Tenure with a separate vector store or retrieval layer, cross-contamination risk migrates to the boundary between systems rather than disappearing. There is no documented managed cloud tier, which means teams that need to move fast without owning infrastructure operations will reach for a competitor like Mem0 or a hosted vector memory service, accepting the drift trade-off in exchange for operational simplicity.

Bottom line

Proxon and Tenure are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Proxon and Tenure?

Proxon is Paid, while Tenure is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Proxon better than Tenure?

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.

Proxon vs Tenure: which should I pick?

Pick Proxon if its pricing model, openness, or platform fit matches your constraints; pick Tenure otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.