UiPath has announced a new Integration Service Connector that gives customers access to Amazon Bedrock, a fully managed service that provides access to foundation models (FMs) via an API to build and scale generative AI applications.
Using UiPath’s connector for Amazon Bedrock, automation developers and citizen developers alike can integrate Generative AI directly in their UiPath Studio and Studio Web automations, using the model of their preference and within Amazon Web Services (AWS), the company states.
The connector supports text/chat capabilities through Amazon Titan FMs and several other FMs from leading AI providers via Amazon Bedrock, including the Jurassic-2 family of multilingual LLMs from AI21 Labs, which follow natural language instructions to generate text in Spanish, French, German, Portuguese, Italian, and Dutch.
Customers can also choose Claude, Anthropic’s LLM, which can perform a wide variety of conversational and text processing tasks and is based on Anthropic’s extensive research into training honest and responsible AI systems.
Graham Sheldon, Chief Product Officer at UiPath, says, “The UiPath connector for Amazon Bedrock is simple to use and brings the power of foundation models to all UiPath customers so they can accelerate building their own Generative AI applications."
“With its open, flexible, and responsible approach, UiPath provides organisations with a comprehensive platform for implementing and harnessing the power of AI-powered automation. This functionality complements our vision for helping customers innovate faster with Generative AI.”
Generative AI is powered by FMs - very large models that are pre-trained on vast amounts of data. According to AWS, “FMs can perform so many more tasks because they contain such a large number of parameters that make them capable of learning complex concepts. And through their pre-training exposure to internet-scale data in all its various forms and myriad of patterns, FMs learn to apply their knowledge within a wide range of contexts.”
In addition, since all data is encrypted and does not leave a customer’s Virtual Private Cloud (VPC), customers can trust that their data will remain private and confidential.
Earlier this year, UiPath also announced that data science teams using Amazon SageMaker, an end-to-end machine learning (ML) service, can now quickly and seamlessly connect Amazon SageMaker-hosted ML models into UiPath business processes without the need for complex coding and manual effort.
By connecting Amazon SageMaker to UiPath, users can interact with deployed models via the connector and use their outputs in their workflows.
Graham Sheldon, Chief Product Officer at UiPath, commented, “Data scientists and data science team leaders are working at the cutting edge, creating powerful new machine learning models to accelerate business performance. At the same time, these professionals are saddled with time-consuming, manual management which slows progress and adds costs."
"By connecting Amazon SageMaker to the UiPath platform, we are helping reduce this complexity with automation. This opens avenues for faster deployment, lower costs, and more opportunities for innovation through machine learning.”