What challenges did Druva face before AI implementation?

Customers faced a manual, high-pressure process to interpret telemetry and documentation during security incidents. Earlier AI workflows still required people to piece together insights and decide next steps. Existing build, train, and deploy AI approaches required constant infrastructure management.

What was the impact of the AI solution?

68% of customer issues are resolved through agent workflows without human intervention. Cyber investigations that previously took 30 to 60 days are completed in minutes. Support resolution is 58% faster when human teams assist. There have been over 17,500 AI conversations across more than 3,000 users.

Source

ProductionEvidence: Medium65/100

Druva transforms data security using Amazon Bedrock AgentCore

Use case typeAutomotive operations automationUpdated Jun 13, 2026

Druva built DruAI, an agentic AI solution to help customers complete cyber investigations and recovery workflows. The solution uses a multi-agent system on AWS with AgentCore Memory, AgentCore Code Interpreter, Amazon Bedrock access to Claude models, voice capabilities with Amazon Nova Sonic, and Bedrock Guardrails. In production, DruAI coordinates 8 to 10 specialized agents across investigation, help, and recovery workflows.

Organization: Druva
Industry: Tech & Comms
Location: United States
Published: May 2026

Reported outcomes

+58%

timeTime & speed

68%quantified impact30-60 daystime

Strategic outcomes

New product / capabilityBuilt an agentic cyber investigation solutionNew product / capabilityCoordinated specialized investigation agentsSpeed & agilityCompleted cyber investigations in minutesCustomer experience & trustResolved issues without human intervention

Catalog median for time & speed deployments: +60% across 143 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 68%

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

68% of customer issues are resolved through agent workflows without human intervention.

Normalized claim

Time: 30-60 days

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

Cyber investigations that previously took 30 to 60 days are completed in minutes.

Normalized claim

Time: 58% increase

AWS Customer StoriesMay 27, 2026Customer storyInferred claimMedium evidence strength

Support resolution is 58% faster when human teams assist.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Druva
Provider: AWS
Maturity: Production
Linked source: AWS Customer Stories

In production, DruAI coordinates 8 to 10 specialized agents across investigation, help, and recovery workflows

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Agentic AI
2Customer Support Automation
3Cybersecurity

Customers faced a manual, high-pressure process to interpret telemetry and documentation during security incidents.
Earlier AI workflows still required people to piece together insights and decide next steps.
Existing build, train, and deploy AI approaches required constant infrastructure management.

Druva designed DruAI as a collection of specialized agents that coordinate cyber investigation, remediation, and recovery workflows.
AgentCore provides secure serverless hosting, request routing to internal tools, session isolation, automated scaling, code interpretation, identity controls, and memory.
Druva uses Amazon Nova Sonic for conversational voice capability and Claude models in Amazon Bedrock for different agent roles, with Bedrock Guardrails for protections.

Technologies

Amazon Bedrock AgentCore AgentCore Memory AgentCore Code Interpreter Amazon Bedrock Amazon Nova Sonic Amazon Bedrock Guardrails Strands Agents SDK

68% of customer issues are resolved through agent workflows without human intervention.
Cyber investigations that previously took 30 to 60 days are completed in minutes.
Support resolution is 58% faster when human teams assist.
There have been over 17,500 AI conversations across more than 3,000 users.

Architecture

DruAI is a multi-agent system built on Amazon Bedrock AgentCore. It uses secure serverless hosting with session isolation and auto-scaling, request routing, AgentCore Code Interpreter for analysis tasks, AgentCore Identity for scoped access to backend systems, AgentCore Memory for personalization and learning across interactions, Amazon Bedrock for model access, Amazon Nova Sonic for voice, Claude Sonnet and Claude Haiku for different agent roles, and Amazon Bedrock Guardrails for prompt-injection and malicious-input safeguards. Druva initially used LangChain and later transitioned to Strands Agents SDK within the AWS environment.

Sources & evidence1

Evidence: Medium65/100Evidence strength

Customer explicitly identified
Deployment status explicitly supported
Primary source available
Quantified outcome available
Technical implementation details available

Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: PrimaryConfidence: High

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

Druva transforms data security using Amazon Bedrock AgentCore

Use case focus

Challenges

Solution

Impact

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