Service and Support
Customer service and support for Workato receive high ratings, with teams providing quick resolutions and helpful guidance. Users praise the efficient technical support, noting responsiveness and the availability of professional service hours. Customer success teams enhance experiences by assisting with initial setups and addressing concerns effectively. They benefit from real-time chat and portal follow-ups, particularly appreciating the structured support levels for both minor and complex issues.
Deployment
Setting up Workato is simple and user-friendly. Users find it easy to connect apps with credentials, run recipes, and deploy integrations via web browsers. Although involving on-premises systems requires a longer configuration process, most features activate upon licensing. Security compliance and internal connections might take time but can be managed with guidance from support and available materials. The setup is designed for minimal effort, allowing swift deployment and broad application possibilities.
Scalability
Workato's scalability is praised, with it being highly adaptable due to its cloud nature, supporting numerous users and applications. Licensing options cater to diverse organizational needs, allowing cost management based on usage. Reports indicate seamless operation, though some experienced limitations with high data volumes. It suits varied business sizes but performs well under most circumstances, even with complex transaction requirements. Maintenance requires minimal workforce once implemented.
Stability
Workato demonstrates stability, particularly for daily operations, with minimal downtime. Several users rate its stability highly, and it runs on AWS, enhancing confidence. However, some challenges include processing limits for large CSV files and platform downtime during deployment, requiring restarts. During high loads, initial data loads may falter. Users appreciate Workato's efforts to enhance stability, and some report no issues. Nevertheless, HTTP request handling and scalability during data processing need improvements according to some experiences.