--- title: "SumizAI vs Skales" url: "https://sumizai.com/alternative-to/sumizai-alternative-to-skales.html" date: "2026-08-14T00:00:00+02:00" modified: "2026-08-14T00:00:00+02:00" description: "Looking for a Skales alternative? SumizAI and Skales side by side: price, licence, platforms and what each one actually does." tags: ["ai notes", "sumizai", "skales", "alternative to Skales"] --- # SumizAI vs Skales Looking for a Skales alternative? SumizAI and Skales side by side: price, licence, platforms and what each one actually does. ## What Skales is Skales is a privacy-first local AI agent that automates browser and desktop app workflows without relying on the cloud. Installation takes about thirty seconds, and the agent runs locally, using either models running on the user's own device or, optionally, models accessed through third-party APIs. All automation logic and data stay on the user's disk, setting Skales apart from cloud AI assistants that require sending every instruction to an external server. Key features: Browser automation lets the agent click, fill in forms, and navigate web pages on the user's behalf, carrying out multi-step tasks without manual intervention at every step. Self-coding Node.js tools mean the agent can generate its own helper code for a specific task instead of being limited to pre-programmed functions. Native integrations with desktop apps extend the reach of automation beyond the browser alone. Support for both local models and API-accessed models gives the flexibility to choose between full privacy and cloud compute power depending on the task. The whole installation process takes roughly half a minute, with no complicated setup upfront. Who it's for: Skales appeals to technical users who want to automate repetitive browser and desktop tasks without sending sensitive data to a cloud AI provider. Developers and administrators who value full control over what happens to their data find a tool that matches their security requirements in Skales. People experimenting with local language models appreciate being able to plug in their own model instead of depending on a single cloud provider. Use cases: In practice, Skales works well for automating repetitive web form filling, for instance when submitting many similar applications to different systems. An administrator can task the agent with regularly checking the status of several internal dashboards and collecting the results in one place, without manually logging into each one. A developer automating manual interface testing can use Skales to walk through typical user paths without writing a separate test script for every scenario. Pricing and business model: Skales is free and open source, with no paid plans or subscriptions at the time of writing. That model is typical of tools built by a technical community where monetization isn't a priority, and the project sustains itself through developer contributions and occasional donations. The lack of fees lowers the barrier to entry for anyone wanting to try local AI automation with no financial commitment. Limitations and what to watch for: Browser automation and self-generated code carry a risk of unintended actions if the agent misinterprets an instruction — it's worth testing new automations on less critical tasks before trusting them with something important. Local models can be weaker than the largest cloud models, so automation quality depends partly on which model the user chooses to run locally. AI notes from local automation: Skales isn't a notes app, but since the agent runs locally and stores data on disk, the results of its work — collected information from an automated page search, for instance — can be manually saved as ai notes in a separate notebook. The agent itself doesn't generate such notes automatically in a format ready to paste into an external notes system. Flexibility of model choice: Being able to switch between a local model and an API-accessed model means the user decides the privacy-versus-quality tradeoff on a per-task basis, not once and for all at install time. A task that doesn't touch sensitive data can use a more capable cloud model, while a task involving confidential company information stays entirely on the device. Open code as a guarantee of control: Because Skales is open source, any technical user can check exactly what actions the agent performs and what data leaves the device, rather than relying solely on a closed tool vendor's claims. That matters for organizations with strict auditability requirements for tools that automate work with data. Automation as a starting point for notes: While Skales doesn't run a notebook itself, many users pair it with a separate notes tool, saving the results of automated tasks there as ai notes ready for further analysis. That two-step flow — Skales performs the task, a separate tool stores its result as a note — works, but requires manually moving data between the two apps. Safety when automating the browser: Because the agent runs locally and has access to the browser, it's worth being deliberate about the permissions it's granted and limiting its scope to trusted sites, especially during initial tests of a new automation. AI notes from such test sessions — recorded observations of what worked and what needed fixing — help build safer automations going forward. A fast start with no setup: The thirty-second install is one of the main arguments for Skales over more elaborate automation platforms that require hours of configuration before the first task runs. That fast start lowers the barrier for anyone who just wants to try local AI automation without a big up-front time commitment. What's worth checking before choosing: Before trusting Skales with important tasks, it's worth testing it on simple, non-critical automations and checking how well it performs with the local model you plan to use day to day. Bottom line: Skales is a local, private agent for browser and desktop automation, built for users who don't want to rely on the cloud. Anyone looking for a tool that automatically turns valuable fragments of AI conversations into ai notes saved as files should consider a tool built specifically around that workflow, since Skales focuses on automating actions, not on notes. Comparison with SumizAI: Skales and SumizAI are tools with different purposes, united by a concern for privacy and local data storage. Skales automates multi-step tasks in the browser and apps, generating code along the way and carrying out actions on the user's behalf. SumizAI focuses solely on one moment — the point where an answer from a conversation with an AI model is worth keeping as a ai notes entry saved as a Markdown file. Anyone needing to automate repetitive technical tasks will reach for Skales; anyone wanting to build an organized archive of ai notes from AI conversations will find SumizAI the better-fitting tool. **Key facts** - Price: Free - License: Open Source - Origin: Austria, EU ## What SumizAI is A note-taking application built around a conversation with an AI model. You ask a question, the answer streams back, and the answers worth keeping become Markdown notes — filed into a vault that is a folder on your own disk. A vault is a directory holding `base.md`, a generated table of contents up to six levels deep, and a `notes/` folder with one `.md` file per note. Before a note is written it is checked against the ones already there, so the fourth note about the same idea gets merged instead of added. Links between notes are ordinary Markdown links to files that exist. The model is never ours: you bring your own API key to one of seven providers — Anthropic, OpenAI, Gemini, Groq, OpenRouter, a local Ollama or your own server — and pay that provider directly. A question sends the table of contents plus at most five relevant notes within a 24,000-character budget, and the app shows you which five it used. ## Where they differ - Both mention AI. The difference is whose key it runs on: SumizAI never resells inference — you connect one of seven providers (Anthropic, OpenAI, Gemini, Groq, OpenRouter, a local Ollama or your own server) with your own API key and pay that provider directly. Check what Skales does with the model bill before comparing prices. - Skales is open source, and SumizAI is not. If reading the source is what decides it for you, that is a real argument for Skales. The guarantee SumizAI offers instead is structural rather than legal: the notes are Markdown files in a folder you chose, so they open in any editor whether or not the application is running. - AlternativeTo's description of Skales does not mention Markdown, so check what format your notes end up in before you fill it up. SumizAI writes standard `.md` files to a folder you picked, and an unpaid account can still export all of them. - Both are run from the EU: SumizAI's operator is registered in Poland and the servers are in Germany. Full side-by-side comparison table and pricing: [https://sumizai.com/alternative-to/sumizai-alternative-to-skales.html](https://sumizai.com/alternative-to/sumizai-alternative-to-skales.html)