How Skynet Compares: One Workspace Against the Stack Most Teams Are Running
The AI tools market is usually compared model by model, which is the wrong unit. Frontier models are converging in capability and leapfrog each other every few months. What does not converge is the shape of the product around them.
Skynet sits on top of the frontier models rather than against them. It routes to GPT, Claude, Gemini, Perplexity, DeepSeek, and Groq, so the comparison worth making is not “which model” but “which workspace”.
Skynet Workspace
One subscription
Every frontier model, one memory, one bill
- Routes each prompt to the best model automatically
- Memory carries across chat, agents, and mini-apps
- Agents act: reply in Slack, open PRs, update Notion
- Deployable on your own cloud or data centre
- One invoice, one admin surface, one seat price
The stack most teams run instead
- One model per subscription: you pick, every time
- Context restarts in every separate tool
- Answers, then the work is handed back to you
- Data leaves your environment by default
- A separate invoice and admin panel per tool
The four axes that decide it
Model coverage. A single-model assistant is only ever as good as its one provider’s current release. Routing across every frontier model means the workspace does not regress when one lab has a slow quarter.
Memory that carries. Context built in a chat is available to the agent and the mini-app. In a multi-tool stack, every tool starts from zero, and the person becomes the integration layer.
Acting, not answering. Reading a Slack thread and replying in it are different products. Skynet’s connectors write as well as read, which is where the time is actually saved.
One bill. Covered in detail in our cost analysis. The short version: consolidation is the single largest line-item saving available to most teams.