Buyers usually compare Onky with Claude Cowork, ChatGPT Enterprise, Sauna.ai, Vybe.build, and Viktor.com. All are good products.
| Capability | Onky.aiEnterprise AI assistant | Claude CoworkProprietary agentic workspace | ChatGPT EnterpriseWorkspace Agents, proprietary | Sauna.aiMultiplayer AI agent platform | Vybe.buildAgent and app builder | Viktor.comAI employee in Slack and Teams |
|---|---|---|---|---|---|---|
| Work and apps | ||||||
| Agentic workspaceA shared workspace where agents and your team get work done together | Native | Native | Partial | Native | Partial | Partial |
| Contextual enterprise answersReads your internal documents and history before it answers | Native | Native | Native | Partial | Partial | Partial |
| Autonomous micro-app generationTurns an unstructured workflow into a working internal app | Native | Partial | Partial | Partial | Native | Partial |
| Persistent org-level memoryRemembers how the company works, not just what you asked | Native | Partial | Partial | Native | Partial | Partial |
| Governance and policy | ||||||
| Policy-enforced agent actionsA default-deny policy engine on every single action | Native | Partial | Partial | Partial | Partial | Partial |
| End-to-end audit trailEvery action logged as evidence for your auditors and DPO | Native | Partial | Partial | Not offered | Partial | Not offered |
| Company IP protectionYour prompts, files, and workflows can never become a model's know-how | Native | Partial | Partial | Not offered | Not offered | Not offered |
| Data confidentialityConfidential by design: no external AI lab in the processing path | Native | Partial | Partial | Not offered | Not offered | Not offered |
| Deployment and infrastructure | ||||||
| Open-source LLM model stackNo lock-in to one model vendor | Native | Not offered | Not offered | Partial | Not offered | Not offered |
| Runs in your own infrastructureYour cloud, on-premise or air-gapped, on request | Native | Not offered | Not offered | Not offered | Not offered | Not offered |
| Predictable cost controlA fixed annual cost available, with no per-token vendor pricing underneath | Native | Partial | Partial | Partial | Partial | Partial |
Scroll the table sideways to see every column.
Proprietary agentic workspace
Anthropic's agentic workspace: excellent reasoning, strong built-in governance, and deep document work with your internal context.
Cowork runs on Anthropic's proprietary models in Anthropic's cloud. Onky runs open-source models with no frontier AI lab in the loop, deploys in your cloud, on-premise or air-gapped on request, and builds the internal apps a workflow is missing instead of stopping at the answer.
Workspace Agents, proprietary
The default workplace AI assistant: broad adoption, strong general capability, and workspace agents across the OpenAI ecosystem.
It is proprietary end to end, and most work still lands back in the chat window. Onky executes across the systems you run, ships what it builds as governed internal apps, and can move the whole platform inside your own perimeter, where proprietary-API models cannot follow.
Multiplayer AI agent platform
A multiplayer AI agent that learns how your team works, remembers context, and runs scheduled work in the cloud around the clock.
Sauna shares Onky's conviction that AI should act, not just answer. Onky adds what a regulated buyer needs on top of that: a default-deny policy engine on every action, an end-to-end audit trail, and deployment inside your own infrastructure. Sauna's site does not say which models process your data; Onky publishes its open-source model stack.
Agent and app builder
An agent and app builder: describe what you need in chat and it builds the agent or app for you.
For Onky, building is one of four jobs, not the whole product. It also answers with context, acts across your systems, and remembers how your organisation works, and everything it builds is registered with the Kernel, our policy engine, before it can run.
AI employee in Slack and Teams
An AI employee that lives in Slack and Microsoft Teams and does the work where your team already talks.
Onky also acts where your team works, but puts an operating layer underneath: policy-checked actions with an audit trail, an open-source model stack with no AI lab in the loop, and the ability to build and govern the internal tools the work needs. Viktor runs on frontier-lab models it does not name, in a cloud it cannot leave, so your work flows through a third-party AI lab; Onky names its open-source models and can run inside your perimeter.
Yes, for teams that want AI to act rather than only answer. ChatGPT Enterprise is a strong workplace assistant; Onky executes across the systems you run, builds the internal tools it is missing, and runs open-source models with no frontier AI lab in the loop, deployable in your cloud, on-premise or air-gapped on request.
Governance and confidentiality. AI coworkers act on your behalf; Onky does too, with a default-deny policy engine (the Kernel) checking and logging every action, an open-source model stack with no third-party AI lab in the loop, and deployment options down to air-gapped.
Because your prompts, files, and workflows go wherever the models run. Proprietary assistants run on the vendor's cloud under the vendor's terms. Onky runs open-source models only, so nothing you share reaches a third-party AI lab or trains a model, and the same stack can run inside your own perimeter: your cloud or your own data centre.
Of the assistants in the comparison grid, only Onky offers on-premise and air-gapped deployment, available on request. That is a direct consequence of the open-source model stack: open-weight models can go where proprietary-API models cannot.
A comparison table tells you the categories. A 30-minute call on your actual workflows tells you the answer.
Book a demo