Leveraging High-Volume Alerts to Derive Actionable Insights with Multi-Agentic AI Solution
Executive Summary
The customer set out to significantly improve its security operations by leveraging the security information to create an autonomous security system. The Security Operations Center faced huge volumes of data making it difficult for the SOC teams to analyze all critical threats. Moreover, this information was siloed and scattered across multiple disconnected platforms. The security teams had to resort to manual processes to investigate and identify emerging threat patterns.
About the Customer
The customer is a leader in Security Service Edge (SSE) and Zero Trust solutions, helping organizations secure with cloud-native security. Their platform provides visibility, real-time data and threat protection, and policy enforcement across cloud, web, and private applications.
Customer Challenge
Security teams faced overwhelming volumes of alerts across multiple security tools, leading to significant operational challenges as mentioned below:
- Overwhelming Alert Volume: Security Operations Centers handling 10,000+ daily alerts across 100+ locations.
- Disconnected Systems: Critical security information siloed across the customer, Okta, Crowdstrike, and other platforms.
- Resource Constraints: Understaffed SOC teams unable to investigate all potential threats.
- Manual Workflows: Time-consuming processes for alert correlation and investigation.
- Reactive Response: Limited ability to proactively identify emerging threat patterns.
These challenges required a new approach beyond traditional security automation—one that could intelligently coordinate multiple capabilities to function as an autonomous security operations system.
Proposed Solution
Crest Data developed a sophisticated Multi-Agentic AI System for the customer, leveraging AWS Bedrock to revolutionize security operations:
Specialized Agent Architecture
The solution deployed multiple collaborative AI agents, each with specific roles:
- Alert Triage Agent: Autonomously evaluates and prioritizes security alerts
- Context Gathering Agent: Collects relevant information across security systems
- Correlation Agent: Identifies relationships between seemingly disparate events
- Response Recommendation Agent: Suggests appropriate actions based on threat analysis
- Documentation Agent: Creates comprehensive reports and maintains investigation records
Agent Orchestration System
The solution provided an orchestration system with below capabilities:
- Sophisticated coordination layer allowing agents to work together on complex investigations
- Dynamic task allocation based on alert severity and system load
- Reasoning engine to determine optimal investigation paths
- Human-in-the-loop integration points for critical decisions
Multi-Agent Implementation Approach
The solution adopted a multi-agent approach to ensure that the system helps solve critical problems:
- Agent Design Phase: Defining specialized agent roles, capabilities, and collaboration patterns.
- Coordination Framework: Building the orchestration system for inter-agent communication.
- Tool Integration: Implementing solution for each security system connection.
- Reasoning Development: Training specialized reasoning capabilities for security analysis.
- Workflow Automation: Creating autonomous investigation sequences across agent teams.
- Human Oversight Integration: Designing effective human-AI collaboration interfaces.
Technologies Leveraged
The solution was built using modern and solid technological stack as below:
- AWS Bedrock
- LangGraph
- Anthropic Claude
- Streamlit
- Kubernetes
About Crest Data
Crest Data is a data and AI-first product engineering and technology solutions provider with deep expertise in cloud and AI, cybersecurity, observability, data analytics, and workflow automation. In this case study, Crest Data applied its CloudOps and DevSecOps capabilities to help the customer migrate from on-prem infrastructure to a secure, scalable, and cost-efficient AWS environment, supported by infrastructure automation and proactive monitoring.
With 1,200+ experts and a track record of 5,500+ successful projects across 150+ global customers, and backed by strong partnerships with AWS, Google, Microsoft, Datadog, Dynatrace, ServiceNow, and NetApp, Crest Data delivers outcome-focused solutions that strengthen security, improve platform reliability, and enable sustainable digital growth.
