Understand this story
Denodo released an independent research study conducted by Veqtor8, titled "Return on Investment of an AI Data Layer Dedicated to Agentic AI." The study shows that after deploying a governed AI data layer, enterprises achieved a three-year ROI of 290%, a 3x increase in agent deployment speed, and a 68% reduction in AI operating costs. The research model covers 100 distributed data sources, with the number of agents growing from 100 in year one to 900 in year three, and the per-task context payload dropping from approximately 18,000 tokens to approximately 5,760 tokens. The study also claims that this data layer can address the proliferation of MCP servers, saving more than 75% in integration and governance costs. Currently, this study has been reported by 21ic Electronics Network, and no additional independent sources have cross-verified it.
AI-generated from public reports
Latest development · Report
Denodo AI Data Layer Study: Enterprise Agentic AI Achieves 290% Three-Year ROI, 3x Faster DeploymentDevelopments
1 confirmed developments
- Source:English text is being prepared.
Reports and discussion timeline
Browse reports and discussion by time. Their evidence levels remain distinct.
Oct 22
21ic Electronics Network
Denodo AI Data Layer Study: Enterprise Agentic AI Achieves 290% Three-Year ROI, 3x Faster Deployment
Denodo has released an independent study conducted by Veqtor8, showing that after deploying a governed AI data layer, enterprises achieved a 290% three-year ROI, 3x faster agent deployment, and a 68% reduction in AI operating costs. The model covers 100 distributed data sources, with the number of agents growing from 100 in Year 1 to 900 in Year 3, and per-task context payload dropping from approximately 18,000 tokens to approximately 5,760 tokens. The study states that this data layer can solve the problem of MCP server sprawl, saving over 75% on integration and governance costs.