Probe0 vs Kosmoy
Kosmoy is bought by a governance or platform team to control AI across an organization, and it runs in that organization's Kubernetes cluster. Probe0 is a local LLM proxy I run on my own laptop to cut what my coding agents spend, and it has no server at all.
An enterprise AI control plane (gateway, governance, observability, agent sandboxing) that organizations self-host in their own Kubernetes cluster.
| Feature | Probe0 | Kosmoy | Edge |
|---|---|---|---|
| Setup for one developer | One local proxy plus a certificate, installed once | Helm chart, Postgres, cluster ops, sales conversation first | Probe0 |
| Where your prompts go | Stay on the Mac. No Probe0 server exists. | Through a gateway your cluster operator runs | Probe0 |
| Coding agent coverage | Claude Code, Codex and Cursor route through it with no per-tool config | OpenAI-compatible base-URL swap; Python SDK for coded apps | Probe0 |
| Caching | Exact cache on local disk plus a semantic cache with a strict similarity floor | Not documented as a shipped feature; discussed conceptually in their blog | Probe0 |
| Semantic cache inside an agent run | Refuses to match anything carrying tool calls | No documented semantic cache to apply | Probe0 |
| Working with no network | Cache hits and local Ollama or LM Studio models serve offline | Gateway is a network service; air-gapped means your cluster | Probe0 |
| Who spent the money | Ledger names the process behind each call, with real cost | Attribution by app, team, environment and use case | Probe0 |
| Judging one optimization on its own | Each module toggles alone and reports what it saved | Dashboards and reports across the org, not per-module | Probe0 |
| Governance and compliance | None. A local request ledger, not an audit artifact. | EU AI Act, ISO/IEC 42001 and NIST AI RMF evidence from registries and gateway logs | Competitor |
Kosmoy is the better product for an organization that has to prove to a regulator what its AI systems do, and I will not pretend otherwise. But the problem I built Probe0 for is narrower and more immediate: one engineer watching an AI coding agent burn tokens on their own machine. Probe0 installs as a local proxy with a certificate you trust once, and after that every coding agent CLI on the machine goes through it, Claude Code and Codex and Cursor, with no per-tool configuration. The request ledger records model, tokens, real cost, latency and which process made each call, so you can see that a background agent, not you, spent most of the afternoon's money. Because Probe0 knows your real usage, it also tells you when your plan tier sits above what you actually consume.
The floor for Kosmoy is a Kubernetes cluster with a Postgres-compatible database, and the entry point is a sales conversation, because there is no free tier, no self-service signup and no open-source core. Probe0 is a sign-in with Google or GitHub and a proxy on localhost. Caching is where the difference shows up in dollars: it is not a documented Kosmoy feature, appearing in their cost-reduction blog as a concept with quoted hit rates rather than on the AI Gateway or LLM Gateway product pages. Probe0 ships two caches. The exact cache lives on local disk and a hit never touches the network. The semantic cache uses a local vector index with a strict similarity floor and refuses to match any conversation carrying tool calls, because a wrong hit inside an agent run corrupts the run in a way that costs more than the tokens it saved.
Underneath that, local routing sends work to a model already loaded in Ollama or LM Studio and retries weak answers on the cloud, model tiering starts cheap and escalates only when the cheap model fails, and request coalescing collapses simultaneous identical calls into one upstream request. The spend guard holds a hard cap per run and per day, warns, and then actually pauses. Every module switches off individually and each reports what it saved, so a change is judged on its own numbers rather than on my claims. The limits are plain: macOS only, private beta, single user, and provider coverage means what coding agents call. Kosmoy's other side of the ledger is equally real and equally out of scope here: registries that pull inventories from Azure AI Foundry, Bedrock, Vertex, Salesforce and ServiceNow to flag shadow agents, IdP group-to-role mapping, in-path PII and injection filters, Action Capsules that sandbox agents with namespaces, cgroups v2, Seccomp and Landlock, 20+ evaluators, red teaming, SIEM export, and named production customers including Banca d'Italia and Leonardo.
The verdict
Buy Kosmoy in exactly one situation: your organization needs audit evidence and guardrails that developers cannot switch off, and you have the cluster and the procurement cycle to get them. Everywhere else, the money is leaking on one laptop at a time, and that is what Probe0 fixes. It installs in minutes, keeps every cache hit and local model call off the network, tells you which process spent what, and pauses the run when the cap is hit. If you are a developer on a Mac running coding agents today, install Probe0.
Questions
- Is Probe0 a Kosmoy alternative?
- Only for the cost-control part. Kosmoy is an enterprise governance and compliance platform for whole organizations, and Probe0 does not attempt inventory, RBAC, guardrails, agent sandboxing or audit evidence. If your reason for looking at Kosmoy is that your AI coding agent bill is too high, Probe0 covers that on one machine.
- Can I run Kosmoy or Probe0 on a laptop?
- Probe0 runs entirely on your Mac and there is no Probe0 server anywhere. Kosmoy has no single-machine or desktop mode; the documented deployment is self-hosted in your own Kubernetes cluster via Helm charts with a Postgres-compatible database, including an air-gapped option.
- Does Kosmoy cache LLM responses?
- Caching is not documented as a shipped Kosmoy feature. Semantic caching appears in their cost-reduction blog as a general technique with quoted hit rates, but it is not on the AI Gateway or LLM Gateway product pages. Probe0 ships an exact local disk cache and a semantic cache that refuses to match anything carrying tool calls.
- How does each one handle local LLM routing?
- Both support local models. Kosmoy lists on-prem vLLM and Ollama alongside the major cloud providers, aimed at organizations running private models. Probe0 sends a request to a model already running in your Ollama or LM Studio, checks the answer, and automatically retries on the cloud when the local answer is weak.