The Sqwibbl approach
Every AI company is racing to build a bigger brain and rent it back to you by the token. We think that's the wrong race. Capability stopped being scarce. Three things are scarce now: whether the AI runs on knowledge someone is accountable for, whether anyone can prove what it did, and whether anything actually got done.
Three things that are actually scarce
A Professional Language Model is a governed knowledge asset — written by a practitioner, owned by a person, a team, an institution or an Enterprise PLM Node, and monetized on PLMMarket.com.
When Sqwibbl answers from a PLM, the answer carries its source and the expert gets paid. That is a different architecture than scraping the web, and it produces a different kind of answer: the one you can defend when someone asks how do you know?
Eight surfaces, one agent. Chat, Day-One Expert, Courses, Projects, Studio, Labs, Skills and Settings all end the same way: work product on disk, not a wall of text.
Consequential actions stop on an Action Card that shows exactly what is about to happen. Take Back returns the desktop to you at any moment.
Sqwibbl is a complete desktop assistant with its own local brain — no account, no network, no PLM required. That matters, because an assistant that stops working when a subscription lapses is not an assistant.
Connected, it becomes the front door to the PLM Network: the client employees use, and the agent your Enterprise PLM Node assigns work to.
The Node governs the knowledge. · Sqwibbl does the work. · The network pays the expert.
Eight surfaces, one agent
Not a roadmap. This is what the agent does on a Windows desktop right now — and each surface ends in a file, a document or a finished task.
Tell Sqwibbl the outcome you want and it does the work on your Windows desktop, asking first before anything that sends, pays, posts or deletes.
Use software you've never used: Sqwibbl gets a step-by-step plan from a PLMMarket manual, carries it out, checks the result and saves it as a reusable skill.
Turn a PLM or PDF into a structured course. Sqwibbl teaches it one lesson at a time, checks your answers and tracks your progress.
Run multi-step work from local plans or tasks assigned by your Enterprise PLM Node. Each project is a saved, shareable chat; consequential steps wait for your review.
Describe a small Windows app and Sqwibbl builds it, launches it and checks it against your definition of done. Apps hold no passwords or keys.
Bounded improvement loops for skills, prompts and documents: scored attempts within a time budget, with results applied only when you approve.
Describe a task and Sqwibbl drafts a reusable skill for your review. Manage installed skills, restore earlier versions and turn skills on or off.
Configure local and frontier AI brains, PLM Network, Google Workspace, MCP servers and AWS, with API keys kept in protected Windows storage.
On a server instead of a desktop? The same agent ships preinstalled on a Windows Server AMI, alone or with an Enterprise PLM Node.
Inside an organization
For teams, Sqwibbl is packaged with an Enterprise PLM Node: the knowledge layer runs in your own AWS account, the agents run on your employees' PCs, and the network settles with the experts whose knowledge was used.
Your documents become PLMs under your access rules, in your VPC. Every agent is a registered principal with an owner, scopes, quotas and one-click revocation.
Agents operate Windows applications, work the projects and tasks their owner can reach, and file weekly activity evidence for review.
A query that draws on a PLM is a royalty event. Knowledge owners are compensated for their expertise, and the answer arrives with its receipts.
Put it to work
Download Sqwibbl, give it a real task, and watch what happens when the assistant has its own brain, a citable source and hands on your computer.
Windows 10 and 11 · free download · no account required to start