Sai is an AI computer-use agent built by Simular for organizing, executing, and repeating real work across applications, websites, and desktop software. Rather than being a narrow chatbot bolted onto a single app, Sai behaves like a robosecretary: it operates a fleet of autonomous computers, understands the state of a screen, and carries out multi-step tasks end-to-end while always asking for your permission before it takes an action that matters. This design lets individuals and teams hand off the tedious, repetitive parts of computer work, the clicking, copying, form-filling, and cross-app coordination, without giving up oversight.
Introduction
Most knowledge work today still involves stitching together dozens of small manual steps spread across browser tabs, spreadsheets, internal tools, and desktop applications. Sai was built to close that gap. It treats the computer itself as the interface, the same way a human assistant would: it can see what is on screen, decide what to click or type next, and move a task forward across as many applications as the job requires. Instead of requiring custom integrations for every tool, Sai works with the software you already use.
Key features
Computer-use automation: Sai directly operates a computer's interface, clicking, typing, navigating menus, and reading on-screen content, so it can complete tasks that span multiple apps and websites without needing an API for each one.
Permission-first execution: Before Sai takes a consequential action, it asks for your permission, keeping a human in the loop for anything sensitive rather than acting silently in the background.
Fleet of autonomous computers: Sai can coordinate multiple virtual computers at once, letting it parallelize repetitive workflows instead of handling them one at a time.
State-of-the-art benchmark performance: Sai achieved the top score on OSWorld 2.0, a leading benchmark for real-world computer-use agents, while running at less than two-thirds the cost of the models it outperformed, meaning stronger results without a proportional increase in compute spend.
Repeatable workflows: Once a task has been demonstrated, Sai can repeat it reliably, which is valuable for recurring operational work rather than one-off actions.
Use cases
Sai is well suited to practical, repetitive computer work: pulling data from one system and entering it into another, filling out forms across web portals, reconciling information between spreadsheets and internal dashboards, monitoring websites for changes, and running multi-step administrative processes that would otherwise require a person to watch every click. Teams can use it to offload operational busywork, while individuals can use it as a personal assistant for their own recurring digital chores.
Benefits
Because Sai operates the same interfaces a person would, teams do not need to build or maintain bespoke integrations for every tool in their stack. The permission-based approach keeps humans in control of important decisions, which makes it easier to trust the agent with real work rather than treating it as a black box. And because Sai's approach is both accurate and cost-efficient, as demonstrated by its OSWorld 2.0 result, organizations can automate more without a runaway compute bill.
Conclusion
Sai represents a practical approach to computer-use AI: it does not try to replace every application with a new API, it simply learns to operate the computer directly, the way a capable assistant would, while keeping people in the loop on anything that matters. For teams and individuals looking to automate real, multi-step computer work across their existing tools, Sai offers a benchmark-leading, cost-efficient way to get there.
