Dinodo announced the unveiling of new integration features linked with AWS's data and AI services, stating that it will support enterprise AI agents in utilizing distributed data more reliably.

On the 19th in Seoul, Dinodo announced product integration capabilities with AWS services such as Amazon SageMaker, Amazon Bedrock AgentCore, and Amazon Quick. This announcement was made based on the assessment that companies are facing issues with data accessibility and control as they apply AI agents to actual business operations.

Enterprise data is often scattered across various environments, including ERP, CRM, manufacturing systems, SaaS, and the cloud. For AI agents to be utilized for business automation or decision support, they must not only locate the necessary data but also manage its meaning, access rights, and usage standards.

Dinodo explained that through this integration, it connects data scattered across on-premises and multi-cloud environments in real time and provides business context through a semantic layer. This enables AI agents to go beyond simply querying data and utilize information that meets organizational standards.

Integration with Amazon Bedrock AgentCore is used to manage authentication, request routing, and access control for AI agents. Dinodo enables agents to access necessary data while maintaining existing data governance policies through support for the Model Context Protocol.

The integration with Amazon SageMaker focused on applying a consistent semantic system to the data. Dinodo stated that it supports a zero-copy approach that minimizes data movement, based on over 200 connectivity features including enterprise systems such as SAP, Oracle, and Salesforce.

In addition, it provides granular control over data sources outside of AWS through attribute-based access control, dynamic data masking, and data lineage tracing capabilities. This offers significant potential for use in industries where data security and regulation are critical, such as finance, the public sector, hospitals, and life sciences.

"Agentic AI cannot be implemented with powerful models alone; it requires reliable and governed real-time data," said Suresh Chandrasekaran, Senior Vice President at Dinodor. He added, "Dinodor and AWS are focused on providing an integrated data foundation to enable enterprises to scale AI agents across their entire data environment."