Appian announced that it has signed a Strategic Collaboration Agreement (SCA) with Amazon Web Services (AWS) to make generative artificial intelligence (AI) more accessible to enterprise business processes. Appian will invest significant resources to find novel ways to combine Appian's native AI capabilities and the Appian data fabric with the large language models (LLMs) provided by Amazon Bedrock and machine learning (ML) capabilities from Amazon SageMaker. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies via a single API, along with a broad set of capabilities organizations need to build generative AI applications with security, privacy, and responsible AI.

Amazon SageMaker is a service to build, train, and deploy ML models for any use case with fully managed infrastructure, tools, and workflows. Appian is designed to automate mission-critical business processes in some of the most innovative, highly regulated, and security-sensitive industries. These customers want to leverage AI while maintaining the security of their data.

They also face shortages of data scientists and increasing information technology (IT) backlog. Appian's private AI approach gives enterprises control over their own data and makes sure their data is not used to train public models that other organizations can use. Appian's low-code AI process platform with its Appian AI Skills capability enables customers to easily incorporate AI into business processes, letting AI and humans work together seamlessly.

By harnessing the capabilities of Amazon Bedrock, Appian gains the ability to host LLMs within customer compliance boundaries and privately customize those models, ensuring that sensitive data remains secure and confidential. Amazon SageMaker allows Appian customers to create, train, and fine tune proprietary AI models using their own data. As AWS AI and ML services are designed with security and privacy best practices, Appian customers can leverage their data to receive more accurate and relevant results from their generative AI applications based on the unique needs of their businesses.