Druva has launched Druva AI Resilience, a platform designed to help organisations recover, govern, and defend AI-powered work systems. The solution addresses challenges posed by AI-driven changes and threats to backup environments. The platform includes backup capabilities for Microsoft Copilot and Claude Code, capturing prompts, responses, and generated files. It features Druva Model Context Protocol, which integrates resilience intelligence into AI tools whilst maintaining enterprise authentication and governance controls. The system also introduces Dru SRE Agent, which monitors backup reliability and identifies issues. Powered by Dru MetaGraph, the platform connects data, identities, and AI activity to help organisations recover from AI-driven changes across systems. Druva serves nearly 7,500 customers, including 75 Fortune 500 companies. The AI Resilience products are available now.

Druva AI Resilience: A new foundation for trusted enterprise AI. July 21, 2026 Ranga Rajagopalan, Chief Product & Marketing Officer AI has evolved beyond being a productivity layer and has become an operational layer for the enterprise. Across cloud infrastructure, SaaS applications, development environments, business workflows, and decision-making processes, AI agents and copilots access data, invoke APIs, modify workflows, generate business content, and execute actions across interconnected systems - at machine speed. That shift creates an enormous opportunity. It also changes what organizations must protect, how disruption happens, and what recovery requires. Today, Druva is introducing AI Resilience, a new pillar of the Druva platform designed to help organizations back up, govern, defend, recover, and accelerate enterprise AI with trusted data, operational context, and cloud-native recovery intelligence. AI changes the resilience equation. Traditional resilience strategies were built for a world where people, applications, and workflows operated at a pace organizations could understand and control. When something went wrong, teams could investigate the issue, identify a clean recovery point, restore data, and move forward. AI introduces a fundamentally different operating model. Autonomous and semi-autonomous systems act through identities, permissions, APIs, connectors, governance relationships, and enterprise datasets. A trusted AI agent may be authorized to perform useful business tasks, but if it's over-permissioned, misconfigured, or compromised, it could delete data, corrupt workflows, or propagate changes across multiple systems at machine speed. At the same time, threat actors can use AI to automate reconnaissance, accelerate credential abuse, generate API-driven attacks, manipulate policies, exploit trusted identities, and coordinate disruption across environments faster than traditional attack methods allow. The result is a compressed timeline from action to impact. What once took hours or days can now happen in just seconds. Trusted context becomes a strategic asset. AI also creates and depends on a new class of business-critical assets. Prompts, contextual memory, vector databases, agent definitions, workflow logic, reasoning history, generated artifacts, governance relationships, and AI-generated business knowledge are quickly becoming operational records. These assets influence how AI systems behave, what decisions they support, what data they use, and how work gets done. If that context is altered or disconnected from trusted governance controls, the impact extends beyond traditional data loss. Organizations risk losing institutional knowledge, decision integrity, compliance continuity, and confidence. That is why AI resilience must go beyond protecting data. It must help organizations preserve the availability, trustworthiness, governance context, and recoverability of the systems, data, and knowledge AI relies on. Watch the video for a closer look at Druva's AI Resilience. The Druva approach to AI Resilience. Druva's AI Resilience strategy is built around four interconnected capabilities: Recover, Govern, Defend, and Accelerate. Together, these capabilities help organizations protect AI-critical assets, detect and contain threats, restore a trusted operational state after disruption, and safely extend trusted data and metadata into the AI ecosystems the business chooses - including Claude, Copilot, and MCP integrations. Recover. Understand what changed, how disruption spread, what can be trusted, and how to safely restore operational state. In the AI era, recovery is not simply about restoring the most recent copy. The most recent state may already be contaminated by autonomous actions, corrupted workflows, manipulated policies, or compromised identities. Organizations need recovery intelligence that can reconstruct activity, identify trusted recovery points, validate that data is clean, and reverse destructive or unintended changes with precision. Govern. Protect the workloads, datasets, operational knowledge, enterprise IP, and governance controls AI systems depend on. This includes AI-critical infrastructure, as well as SaaS data, cloud object stores, prompts, context documents, generated content, workflow logic, vector stores, and other artifacts that shape AI behavior and business outcomes. By treating these assets as recoverable business records, organizations can maintain governance continuity and improve confidence in AI reliability. Defend. Detect and contain AI-driven or identity-based threats before they compromise backup resilience or operational continuity. AI can enable machine-speed automation, abnormal API activity, policy manipulation, and recovery sabotage. Druva helps teams monitor backup telemetry, detect unusual behavior, identify policy drift, strengthen identity-aware visibility, and support containment workflows that reduce blast radius before widespread impact occurs. Accelerate. Innovate faster with chosen AI ecosystems, copilots, agents, and workflows. Enterprises should not have to compromise governance or recoverability to adopt AI. By extending the value of protected data, metadata, and recovery intelligence into approved AI ecosystems, Druva helps teams operationalize AI with greater trust, visibility, and control. Powered by Dru MetaGraph. At the center of Druva's approach is Dru MetaGraph, a graph-based intelligence layer that connects backup-derived metadata, identity context, permissions, governance relationships, workload context, operational telemetry, and recovery history across the Druva platform. This connected context matters because AI-driven incidents rarely begin with a simple recovery request. Teams may start with an identity, an API token, an AI agent, a timestamp range, an affected SaaS object, or a sequence of anomalous changes. From there, they need to determine what changed, who or what initiated the change, how far it propagated, which systems were affected, and what can be safely recovered. Dru MetaGraph helps bring those relationships into a unified operational view. Instead of stitching together fragmented tools and disconnected evidence during a high-pressure incident, organizations can use trusted context to investigate risk, validate recovery options, and restore with confidence. Additionally, as part of this broader launch, Druva is also introducing Dru SRE Agent, a new AI-powered capability designed to help organizations move from backup monitoring to continuous backup reliability. Inspired by modern Site Reliability Engineering principles and powered by DruAI and Dru MetaGraph, Dru SRE Agent continuously evaluates backup health, correlates operational signals across workloads, identities, policies, recovery operations, and platform telemetry, and provides prioritized recommendations to help teams identify issues, understand root causes, and take corrective action faster. For AI Resilience, this matters because reliable recovery starts with reliable backups. By proactively strengthening backup health and recovery readiness before disruption occurs, Dru SRE Agent helps organizations build greater confidence that their recovery foundation will be ready when it matters most. Resilience as the foundation for enterprise AI adoption. The organizations that scale AI fastest will not simply be the ones with the most advanced models. They will be the ones with the confidence to operationalize AI safely. As AI becomes embedded into enterprise operations, resilience must evolve from preserving data alone to preserving the trusted context that makes data usable, governable, explainable, and recoverable. Druva AI Resilience gives organizations a foundation for that future. With a fully managed cloud-native SaaS platform, secure-by-design architecture, air-gapped and immutable protection, data-powered detection and response, recovery intelligence, and Dru Metagraph, Druva helps customers protect what powers AI, defend against AI-driven threats, recover from autonomous disruption, and accelerate innovation across the ecosystems they already trust. The AI era will reward organizations that can move quickly without losing control. With Druva AI Resilience, enterprises can adopt AI with greater confidence, knowing their data, context, governance, and recovery foundation are built to keep pace.

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