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Simular is building the world’s first autonomous computers—systems that can use software like humans do.
From browsing websites and filling out spreadsheets to running creative tools and managing workflows, Simular enables a new era of human-computer interaction where software operates itself.
Whether you’re a solo founder, a global enterprise, or an AI researcher, Simular gives you access to the future of computing: computers that think, act, and get things done—autonomously.
This is the 5th launch from Simular. View more
Sai
Launching today
Sai is the world's first robosecretary that works with a fleet of autonomous computers, doing your endless screen work. Each computer navigates software the way you do: reads the screen, clicks the button, types in the form. Trained to interact with the computer interface, Sai automates software even when they lack APIs: legacy desktop apps, internal portals, anything behind a login. Sai supports Windows, macOS and Linux. 73% on OSWorld.
Free
Launch Team / Built With
Simular
Hey Product Hunt 👋
I'm Ang and I build Sai at Simular.
Sai is the world's first robosecretary that comes together with a fleet of autonomous computers doing your endless screen work. We believe the future of work isn't just one computer — it's many computer.
Each computer navigates software the way you do: reads the screen, clicks the button, types in the form. That's the whole point. Because Sai works at the interface layer, it automates things that have no API and never will — legacy desktop apps, internal portals, anything behind a login. Windows, macOS, and Linux. 73% on OSWorld.
What that buys you in practice:
🖥️ Real computers, not a chat box. You hand over a task, it runs it on an actual desktop. Open the workspace any time to watch, or take the mouse back mid-run.
🔁 It learns the route once. Any finished task can be saved as a skill, scheduled, or triggered by an event — so the tenth run is faster and cheaper than the first.
🔒 Autonomy with a seatbelt. Tiered approvals, "trust for this task," and encrypted input for passwords and codes — the model never sees plaintext.
The agent we actually optimize for is whether it's still useful and affordable the tenth time you ask.
Tell us the screen work that eats your week — we'll tell you honestly whether Sai can take it off your hands.
Simular
I'm Chenchen, engineering lead for Sai at Simular. My job is making sure it keeps working after the demo ends.
Most AI agents you've seen run on one machine, in one happy path, in a video. Sai runs on a fleet of real cloud computers. Hand it five tasks and five machines wake up, open the apps, read the screens, click, type, and check their own results. That's the product. It's also the hard part.
What we actually spent the last six months on:
Reliability at fleet scale. Machines sleep, restart, update. An agent that only works when everything is healthy isn't useful. Sai has to wake machines on demand, recover mid-task, and never let two agents grab the same computer.
Seeing the screen efficiently. Sai uses Smart Snapshot: it reads what's on screen with far fewer tokens than raw screenshots, without losing accuracy. That's where most of the cost savings come from.
Making it cheap enough to give away. A screen-driving agent is expensive by default. We got the cost down far enough to ship a free plan.
The number I care about: on OSWorld 2.0, Sai scores 73%, ahead of Claude Opus 5 (70.6%) and GPT-5.6 Sol (62.6%), at $15.70 per task vs their $23.70 and $26.62. Public benchmark, and the cost is what made the free tier possible.
Sai has been in production with real users for six months before GA. Ask me anything about running agents at scale. I'll be here all day.
I'm Li Hau, engineer at Simular.
I spent years building apps that assumed a human would be sitting there doing the clicking. Then I watched how people actually work: twelve tabs, three apps, copying a value from one into another, all day. The interface was never the product — the tasks were.
So we built Sai, a robosecretary, and give Sai a fleet of autonomous computers. Each computer runs command, navigates app, check its own work. What you can do on a computer, can be done by Sai's computer.
The hardest and coolest part wasn't one agent. It was many. Running a fleet of autonomous computers in parallel — keeping them coordinated, recoverable, and honest about what they actually did — is where most of our engineering went.
I'll be in the comments all day — especially happy to talk about the failure cases.
CapCut AI Suite
My work rarely stays in one tab. I go from email to a native app to a spreadsheet just to finish one request. If Sai is able to work across the desktop, then it will be very useful to me.
Simular
@lavana_cricko Hi Lavana, that's exactly the workflow Sai is built for. It operates at the OS level instead of through app-specific APIs, so it can move from your inbox to a native app to a spreadsheet in the same session, the same way you would.
Do you have any becnchmarks for accuracy on common tasks like booking or form filling?
Simular
@mikkellarsen Hey Mikkel, great question. Sai achieved a 73% success rate on the OSWorld 2.0 benchmark, outperforming models like GPT-5.6 Sol and Claude Opus 5. Common tasks like booking and form filling, multi-step flows across apps, are exactly what that covers. Try Sai and let us know how it goes!
Lessie AI
When an automation makes a mistake, the first thing I want is a clear record of what happened. A run history is a useful part of the product, not an extra for admins.
@alexia_li yes, i've been using it daily personally, to view all the task result at a glance is a lifesaver
Triforce Todos
Hey @Simular team, how does it handle logins that need 2fa or otp, does it just get stuck there?
@abod_rehman for now, we do not have access to your authenticator or your phone for 2FA, but we are working on bringing SAI to your phone as well. 😊