Inserting probabilistic models in deterministic workflows for robotic process automation and supervisor system

This invention makes automated business processes (RPA) smarter by letting them use unpredictable machine learning models alongside their usual step-by-step instructions. A separate 'supervisor' system constantly watches these mixed processes, and if the machine learning part starts making errors or behaving unexpectedly, it can automatically intervene to fix, disable, or roll back the system. The claims specifically focus on creating a standard RPA workflow and then either adding a probabilistic workflow to it or collecting data from it.

Why it matters: The explosion of generative AI and large language models since 2022 has made integrating sophisticated probabilistic models into workflows more feasible and powerful, while simultaneously increasing the critical need for robust supervisor systems to manage their non-deterministic outputs.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, machine learning models, RPA system

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