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New Release Announcement: Unveiling the Newest Automation Accelerators (May 2024)

Workato employee
Workato employee

Based on the feedback from the customers and pain points that we heard from the partners, we have released the below 2 new platform accelerators:

  1. Autonomous Operations Framework (AHQ): The Autonomous Operations Framework (AOF) Accelerator was built to provide our customers with a standardized approach for error handling and recovery across all of their recipesWhile the product contains many features to handle errors, organizations often wish to ensure a standard approach is used for all recipe builders to save time and also ensure that the teams supporting the integrations/automation know exactly what will happen when an error is encountered in a recipe. For example, it might include a ticket being created in ServiceNow, a message being logged in a database, and automatic retries of the recipe every 10 minutes. The operations team can configure the settings in the AOF, and then all developers simply send their errors to the framework and all notifications, logging, and retries will be handled automatically
  2. Automation Quality & Security (AHQ): Workato’s Automation Quality & Security AHQ Accelerator provides a framework to standardize recipe development best practices and report on the non-adherence of recipes/deployment packages concerning the defined best practices. This accelerator solves some of the compliance check problems as there is:
    • No easy way for IT to check adherence to best practices.

    • No metrics to identify non-adherence to best practices.

    • No easy way for recipe builders to know whether they are adhering to internal best practices set by IT.

    The Latest Version of AQS has a Completely Redesigned Rules Engine to Perform Quality Checks & Compile Quality Scores from an SDK for all the Rules to Reduce Execution Time & Task Consumption by the Accelerator. Additionally, AQS has unveiled a new SDK designed for Task Optimization Assessment. This SDK can systematically compile recommendations by leveraging insights derived from its predefined rules and core logic, ultimately reducing your task utilization. It significantly accelerates quality check time by 95% while reducing task consumption by 81%.

Would you like to see a demo for any of the accelerators? Get in touch with us through