Frequently Asked Questions

A Windows desktop application can be automated by completing actions through the user interface just like a person would.

This means opening screens, clicking, entering data, reading information and checking that each step actually worked.

Minicor turns this person-like process into something you can trigger through an API without any engineering needed.

The API you're using may not have all the functionality you need. For example, read-only access or a mismatch between what the API does and how the UI needs to receive information.

When functionality isn't adequate, you can build automations that use the application's interface like a human would. Minicor builds these as automations and hands them over as API endpoints, usable just like any other modern integration.

Use the software's API when it supports what you need, and fall back to desktop automation when it doesn't.

The best desktop automation configurations run known tasks without AI, and only bring AI in when judgment is needed, like fixing an error or adjusting to a screen that changed.

Minicor combines both approaches to desktop automation and hands you a single API endpoint that AI products can use.

Look for a platform that gets the job done correctly, catches its own mistakes, and lets a person step in when something goes wrong.

That means it checks every action worked, keeps a clear record when something fails, and can hand off to a human if it gets stuck.

Minicor does all of this, plus secure logins, extra login steps like a text code, video of every run, and an easy way to add more automations without more work to manage them.

Silent failures are prevented by checking that each action actually worked.

For example, after entering a value, the automation should confirm it shows up correctly on screen, so one wrong action doesn't quietly derail everything that happens after it.

Minicor verifies every step and logs it with video replays, so failures are easy to catch and inspect.

Scaling from a few bots to hundreds is an infrastructure challenge, not just an automation one.

It means managing machines, sessions, routing, scheduling, failures, and monitoring, since every new bot adds more to maintain.

Minicor handles this with pooled virtual machines, automated routing, health checks, and monitoring for every bot, keeping the engineering load low as you scale.

Self-healing RPA fixes itself when it hits an unexpected roadblock.

Instead of failing outright, it checks the current screen, figures out what changed, and takes the best next action, like entering data into the correct field.

Minicor runs known steps with pre-set code, and only brings in an agent when something unexpected happens, correcting and verifying the fix worked before moving on.

A computer-use agent operates an application the way a person would.

It reads the screen, moves the cursor, clicks buttons, and types into fields, instead of relying on an API.

This makes computer-use agents useful for older systems and other applications without modern automation support.

Computer-use agents can be slower because they repeat the same multi-step process for every single action.

Each step means capturing the screen, interpreting it, deciding what to do, then acting, which adds time at every point in a process.

Minicor avoids repeating this process for known tasks. Once a known set of actions is set, it runs the same way every time, with no re-interpreting needed.

Computer-use agents can do production work, but reasoning through every action adds uncertainty that builds up across a workflow.

Production systems need verification, visibility into what happened, recovery options, and clear limits on what the automation should do.

Minicor runs common actions the same way every time, and only uses an agent for judgment calls, like fixing or recovering an automation when a screen changes.

RPA and computer-use agents solve automation differently.

RPA follows a set path, which is fast and reliable but can break when the interface changes. A computer-use agent reasons from what it sees, so it adapts better, but takes more time and computing power to run.

Minicor combines both: pre-set execution for the known path, and agent-driven recovery when something changes.

No, a computer-use agent shouldn't reason through every click.

That kind of reasoning is slow and costly, making it a poor fit for an entire set of tasks.

Minicor runs known automations with pre-set code, and only brings in an agent when something unexpected happens, like a moved button or a screen that won't load.

Citrix and Remote Desktop applications can be automated using what's shown on screen.

Since you can't reach the code behind the application directly, automation identifies controls, enters data, navigates workflows, and checks the result, just like a person would.

Minicor runs known tasks in a pre-set way and brings in agents when something unexpected happens, like a moved button or a new authentication step.

Citrix automation is difficult because bots expect information that Citrix doesn't provide.

Traditional automation bots often rely on selectors, element IDs, accessibility information, or other structured information about an application's interface.

In Citrix, that structure may not be available because the automation only receives the rendered screen. This makes selector-based automation uncertain and unequipped to deal with slow run times, resolution changes and session timeouts.

Minicor runs known tasks in a pre-set way and brings in an AI agent to help when that pre-set path changes.

Reliable Citrix automation needs to know the state of its own session.

That way, it can respond to disconnections or timeouts instead of continuing to click on a blank screen.

Minicor keeps session state, credentials, and re-authentication built into the process, so it can recover from disconnects and pick up where it left off.