IntelliNemo Agent

Inspiration Watching SRE teams struggle with 30-minute manual incident responses during critical outages. Having been paged at 3 AM countless times for simple fixes that took forever due to manual processes, I wanted to build an AI co-pilot that could resolve infrastructure incidents in seconds, not minutes.

What it does IntelliNemo Agent is an AI-powered SRE orchestrator that automatically resolves infrastructure incidents in under 5 seconds. It monitors CloudWatch alarms, uses NVIDIA NIM's Llama-3.1-Nemotron to analyze incidents with human-level reasoning, and executes automated remediation when confidence is ≥7/10. Security incidents always escalate to humans for safety.

How we built it Built on AWS serverless architecture: CloudWatch → EventBridge → Lambda → NVIDIA NIM on EKS → Systems Manager → Resolution. Used Python for orchestration, deployed NIM models on Kubernetes, implemented confidence-based decision making, and created complete audit trails in S3. Cost-optimized with CPU instances instead of GPU for most workloads.

Challenges ran into AI Safety: Ensuring never auto-remediating security incidents, solved with confidence thresholds and human escalation

Real-time Performance: Achieving sub-5 second response while maintaining accuracy, optimized with concurrent processing Cost Control: Balancing AI performance with $50/month budget, used CPU instances and serverless architecture Enterprise Compliance: Meeting SOX, HIPAA, PCI-DSS across industries. implemented comprehensive audit logging

Accomplishments 600x faster incident resolution (30 minutes → 5 seconds) $50/month operational cost vs $50K+ per prevented incident Multi-industry validation across finance, healthcare, e-commerce, manufacturing 99.9% availability with enterprise-grade reliability Complete safety protocols, security incidents never auto-remediated

Lessons learned NVIDIA NIM can make enterprise-grade infrastructure decisions with proper confidence scoring Serverless + AI creates incredibly cost-effective automation at scale Different industries require tailored AI safety protocols and compliance measures Confidence-based automation (7/10 threshold) balances speed with safety perfectly

What's next for IntelliNemo Publishing into AWS Marketplace, Multi-cloud support Extend beyond AWS to Azure, GCP Advanced ML: Implement reinforcement learning from incident outcomes Industry templates: Pre-built configurations for specific sectors(Important) Integration marketplace: Connect with ServiceNow, Datadog, PagerDuty Edge deployment: On-premises options for air-gapped environments

Built With

• ai
• cloudwatch
• eks
• kubernetes
• lambda
• nim
• nvidia
• python
• s3