Abstract: In an embodiment, a method includes receiving a first prompt for a large language model (LLM) and categorizing the first prompt into a category based on a topic modeling algorithm. The method also includes processing the first prompt to remove information determined to be irrelevant to the category. The method also includes retrieving one or more historical prompts for the LLM based on a determination that the one or more historical prompts are similar to the first prompt. The method also includes identifying, based on a feedback model, at least one historical prompt as producing an accurate response from the LLM. The method also includes generating a final prompt for the LLM based on the at least one historical prompt. The method also includes providing the final prompt to the LLM.

Abstract: In an embodiment, a method includes receiving bot presence data from a bot discovery agent executing in a computing environment. The method also includes determining, based on the bot presence data, whether an unauthorized bot is present in the computing environment. The method also includes, responsive to a determination, based on the bot presence data, that an unauthorized bot is present in the computing environment, automatically initiating a remediation workflow relative to the unauthorized bot.

Abstract: In an embodiment, a method includes receiving information identifying an input bot for testing. The method also includes detecting a functionality performed by the input bot. The method also includes creating a plurality of inputs for simulation of the functionality of the input bot. The method also includes executing the input bot a plurality of times using a same sample of actions. The method also includes checking for consistency of at least one of behavior and output for the same sample of actions. The method also includes executing the input bot a plurality of times using different samples of actions. The method also includes generating an execution plan for the input bot. The method also includes automatically validating the input bot, where the validation results in an automated determination of whether the input bot is defective.

Abstract: In an embodiment, a method of real-time process monitoring includes initiating monitoring of user interface (UI) activity in a plurality of user environments in which a user-executed process is performed. The user-executed process is defined in a stored instruction set that identifies a plurality of steps of the user-executed process. The plurality of user environments include a first environment operated by a human worker and a second environment operated by a bot. The method also includes, responsive to the initiating, detecting a new process scenario for the user-executed process. The method also includes determining new bot logic for the new process scenario. The method also includes causing the bot to implement the new bot logic.