Dru AI
AI that doesn’t just answer questions, it acts on them. Dru AI is Druva’s agentic AI suite for IT, security, and compliance teams who need to move from insight to outcome, fast.
From Copilot to Agent
Most AI tools surface information and wait for a human to act. Dru AI is different.
It is built on Amazon Bedrock AgentCore and powered by Dru MetaGraph, it understands relationships across your environments and acts on them.
Investigations that took days now take minutes. Routine tasks run on a plain-language prompt.
Recovery workflows that required expert coordination execute in a single step.
Capabilities
Deep Analysis Agents
Long-running AI agents that independently work through complex, multi-step investigations — correlating signals across backups, identities, configurations, and telemetry, then producing formatted findings ready for security, compliance, or operations teams. Investigations that previously took days now complete in approximately 8–10 minutes.
Conversational Intelligence
Ask questions in plain language across backup health, posture, trends, and change history — without building queries or navigating dashboards manually. “Show suspicious admin activity over the last 48 hours and list impacted resources.” DruAI surfaces the answer.
Agentic Memory
DruAI stores and recalls context across sessions, learning your organisation’s environment, terminology, and priorities over time. Fewer repetitive setup steps, faster answers, and investigations that get smarter with use.
Action Agents
Restore entire applications, including configuration, volumes, and networking, from a single natural-language command. For example, recovering an EC2 instance end-to-end without manually coordinating each component.
Compliance & Lifecycle Agents
Surface compliance risks in real time through natural language: “Which workloads are out of compliance with our retention policy and why?” Identify orphaned accounts, retention violations, and policy gaps without waiting on manual reporting cycles.
Secure Sandbox
Test AI prompts, simulate recovery scenarios, and evaluate outputs using built-in synthetic datasets, before deploying any AI-driven action in a live environment.