Agentic AI is transforming all aspects of IT, including data protection and cyber recovery. The key question for backup vendors today is not whether they use AI, but how. The difference in methodologies is significant, presenting a clear choice: an AI that aids your work or an AI that executes the work independently.
The Shift to Agentic AI
The challenge with AI in data protection and security goes beyond detecting threats or surfacing insights and requires understanding relationships across both the environment and data. How applications depend on each other, which users touch what data, and how policies cascade across systems. This requires a fundamentally different data foundation—one that maps connections, not just individual snapshots. With that contextual intelligence in place, agentic AI can safely act on your behalf, not just advise you.
Two Philosophies
The traditional approach gives you AI capabilities to work with. The other delivers AI that does the work. Let’s dig deeper.
Veeam: The Advisory Approach
To date, Veeam has focused its AI on providing advisory assistance to human operators. It embeds machine learning into the data path for tasks like real-time ransomware detection and offers an "Intelligence" chatbot that looks at documentation, not the customer environment, to answer questions and summarize product documentation.
This assistant helps end users navigate and harden a complex, customer-managed infrastructure. But at the end of the day, the Veeam AI chatbot isn’t providing account-specific assistance. This model requires ongoing human oversight for infrastructure management, capacity planning, and optimization decisions. You remain responsible for the infrastructure, capacity planning, patching, and hidden costs, such as cloud egress fees for restores.
Druva: The Agentic Approach
Druva has a long history of providing AI capabilities at the pace of AI innovations. Organizations have used Druva’s Dru Insights and Dru Investigate in production and got tremendous value. Druva continues to innovate and is keeping pace with AI innovations and now has "agentic" AI capabilities built in the platform. AI shouldn't just advise; it should act. Druva's agentic AI turns your backups into a true data intelligence layer—continuously analyzing relationships across your environment to surface risks and automate remediation. Because it's delivered as pure SaaS, this intelligence evolves automatically without infrastructure overhead.
At the core of our Agentic AI engine lies Dru MetaGraph, a graph-powered foundation, built with Druva’s expertise and understanding of backups and data, that maps the relationships across both your backup metadata and the larger environment. Built on years of AI development—from Dru AI to Dru Assist to Dru Investigate—this is an architectural evolution from AI that informs to AI that acts. This allows our DruAl agents to go far beyond simple Q&A, creating analysis dashboards and interactive tabs you can click after an initial query:
Think of it this way. Traditional AI is like a GPS suggesting the fastest route based on traffic data. It gives you a recommendation. Agentic AI is like a self-driving car. It takes your destination, plans the route, and then actively navigates and adjusts in real-time, even taking corrective actions if needed, all while keeping you informed.
Druva is delivering this today with a growing suite of agents:
- Action Agent: There are many types of actions an action agent can perform, and all actions require user approval. One example is restoring a complex, multi-component application from a single natural-language sentence. Future action could include creating or modifying a policy with user approval.
- Insights & Lifecycle Agents: Proactively surface risks by asking questions like, "Show me stale data from orphaned accounts". They automate governance and identify compliance gaps before they become problems.
- Help Agent: Provides conversational guidance to walk you through investigations and complex tasks
This represents a fundamental architectural shift in how AI interacts with backup data. It's a new way of operating. Born in the Cloud and SaaS architecture matters. You just cannot scale AI with on-prem infrastructure. Because Druva is a true SaaS platform, this intelligence comes with zero operational burden. No infrastructure to patch, no capacity to plan, and no surprise egress fees.
What This Means for You
Druva's agentic approach is already delivering measurable results: more than 3,000 customers have used DruAI to investigate and resolve issues, with 63% of customer problems resolved directly by AI without human intervention. Support cases that do require human help are resolved 58% faster thanks to AI-powered telemetry context.
Instead of spending hours manually piecing together infrastructure components during recovery, Action Agents can restore entire applications—like an EC2 instance with all its configuration, volumes, and networking—from a single natural-language command. For compliance teams, the Lifecycle Agent can instantly surface risks by answering questions like "Show me data that is not compliant to PCI retention adherence" or identify orphaned accounts before they become security vectors—eliminating the need to wait days or weeks for data analysts to pull reports from siloed systems.
This momentum is accelerating. Druva's roadmap targets even greater efficiency: reducing cyber investigation time by up to 70%, handling 90% of routine data protection tasks through conversational AI, and turning hours-long troubleshooting into minutes-long resolutions.