Sai

Sai is an AI robosecretary from Simular AI, described as the world's first robosecretary that works with a fleet of autonomous computers. Its purpose is to do your endless screen work, taking routine tasks off your plate so you can focus on other things. Each computer in the fleet navigates software the way you do: it reads the screen, clicks the button, and types in the form. Sai is built to get real work done across apps, websites, and desktop tools, and it is aimed at anyone who spends their day repeating the same clicks and keystrokes across the software they already use. Much of the software people depend on every day was never designed to be automated. Legacy desktop applications, internal portals, and tools that sit behind a login often have no API at all, which means conventional integration and automation platforms simply cannot reach them. The result is endless manual screen work: opening the same screens, copying the same values, filling in the same forms, and clicking through the same flows, hour after hour. That work is repetitive, it consumes attention, and it rarely stops. Sai's answer is to automate the computer interface itself, so the work gets done in the software as it already exists, without waiting for an API, a plugin, or a rebuild. The core of Sai is a fleet of autonomous computers that interact with software the way a human operator does. Each computer reads the screen to understand what is in front of it, clicks the button it needs, and types into the form it needs to fill. Sai has been trained to interact with the computer interface itself rather than with a fixed set of named integrations, which is why it can be put to work in software it has never seen before. This screen-level approach is what lets the system handle interfaces that were only ever meant for a person, turning ordinary clicking and typing into an automated, delegable workflow. Because Sai operates at the interface level, it automates software even when that software lacks an API. The examples given are legacy desktop apps, internal portals, and anything sitting behind a login — precisely the categories that are hardest to reach with traditional automation. Instead of asking for a connector or a developer-written script, Sai works with what is already on screen. For teams that have long been told their tools are not automatable, this removes the biggest blocker: if a person can log in and use the software, Sai can work in that software too. Sai supports Windows, macOS, and Linux, so the same robosecretary approach can be applied across the operating systems an organization already runs rather than forcing everything onto a single platform. It also reports a score of 73% on OSWorld, a benchmark for computer-use agents, giving a concrete, measurable signal of how well it performs on real desktop tasks. Combined with the fleet model, in which one commander can direct multiple autonomous computers, Sai is designed to scale routine screen work rather than handle only a single task at a time. The workflow Sai describes is deliberately simple: you sign in, and you start delegating. Sign-in is offered through Google, and from there you hand tasks to the fleet rather than performing them yourself. Sai commands the autonomous computers, each of which works inside real applications, websites, and desktop tools by reading the screen, clicking, and typing as needed. Because the fleet is made up of multiple computers, routine work can be taken off your plate in parallel rather than one task at a time. The result is an assistant whose unit of work is a computer session, not just a chat message. The benefit Sai promises is straightforward: routine work is taken off your plate. Instead of you reading the screen, clicking the button, and typing into the form, the fleet does it. That matters because the work being automated is the work that never appears on a priority list yet consumes the most hours. By operating software exactly as it is, Sai also avoids the long setup cycles that come with building bespoke integrations, and by supporting Windows, macOS, and Linux, it can fit into the environments people already use. The outcome is time returned, fewer repetitive screen tasks, and less dependence on whether a given tool happens to expose an API. Concrete scenarios follow directly from the capabilities described. Teams can use Sai to drive legacy desktop applications that have no modern interface or API. It can work inside internal portals, the behind-the-login systems that employees use daily but that no outside automation tool can reach. It can complete tasks in anything that sits behind a login where a human would normally sign in and click through screens. More broadly, it can handle work across apps, websites, and desktop tools, which means a single delegated task can span the mix of software a person actually uses during a working day. Sai is presented as a robosecretary for anyone with routine screen work to delegate, and its supported platforms are explicitly Windows, macOS, and Linux. Its maker is Simular AI, and the product is accessed by signing in, with Google sign-in supported, and by continuing through the product's Terms of Service and Privacy Policy. No pricing or plan details are stated in the available content, and aside from Google sign-in, no third-party integrations or technology stack details are disclosed. Sai's primary value proposition is simple to state: it is a robosecretary that runs an autonomous computer fleet so that routine screen work gets done without you doing it. By reading the screen, clicking, and typing the way a person would, Sai reaches legacy desktop apps, internal portals, and anything behind a login that APIs cannot touch, across Windows, macOS, and Linux. Sign in, start delegating, and let the fleet take the repetitive work off your plate.