Autonomous AI Agents for Your Full-Stack Infrastructure. Deploy, Manage, and Scale complex AWS Stacks using LMD-driven autonomous agents. Powered by Amazon Bedrock Agents and AWS Step Functions.
Our agents understand your requirements through natural language and automatically generate AWS CDK or Terraform code. Powered by Amazon Bedrock Agents and AWS Step Functions, enabling 24/7 stack monitoring and self-healing capabilities.
Our RAG engine indexes and analyzes AWS comprehensive documentation including Developer Guide, API Reference, and AWS Well-Architected Framework best practices. Using Amazon OpenSearch with 10M+ vector embeddings, we provide real-time recommendations based on the latest cloud infrastructure patterns. Currently fine-tuning Llama 3 model via Amazon SageMaker to specialize in cloud operations intelligence.
AI-Powered Security Guardrails ensure every deployment complies with AWS Well-Architected Framework standards. Including IAM Role optimization, VPC security scanning, and AWS CloudTrail logging integration for comprehensive governance.
Watch how our AI agents analyze, plan, and execute cloud infrastructure deployment. The interactive terminal shows the step-by-step reasoning process as the agent transforms natural language into production-ready AWS stacks.
"Deploy a high-availability LLM inference environment"
Analyzing AWS region latency & cost...
Querying EC2 price API: us-east-1 Spot pricing is 40% lower than On-Demand for G5 instances
Configuring Multi-AZ high availability...
Detected subnet distribution imbalance. Auto-calculating cross-AZ configuration to meet 99.99% SLA requirement
Applying security guardrails...
Running IAM Access Analyzer: 3 privilege escalation issues detected and automatically fixed
Cost optimization analysis...
Cost projection: $847/month vs standard $1,428/month - 40% savings via Spot instances
Configuration complete
EC2 Fleet with Auto Scaling, Multi-AZ RDS, and encrypted EBS deployed. Ready to generate CDK code
Comprehensive guides, API references, and example implementations for integrating StackAgent Pro into your cloud infrastructure.
Natural language or structured commands processed by LLM agent
LLM inference with tool calling and reasoning via Amazon Bedrock
Serverless compute layer executing infrastructure changes and validation
Infrastructure as Code deployment and resource provisioning
Audit logging and feedback loop for continuous agent improvement
import boto3
from stackagent import Orchestrator, CostOptimizer
# Query EC2 pricing API for cost-aware deployment
ec2 = boto3.client('ec2')
prices = CostOptimizer.get_spot_prices(
instance_type="g5.2xlarge",
region="us-east-1",
az_distribution=True
)
stack = Orchestrator.deploy(
agent_type="cloud_orchestrator",
infrastructure="aws_cdk",
spot_instances=True,
multi_az_ha=True,
iam_access_analyzer=True
)
stack.execute("Deploy high-availability LLM inference environment with cost optimization")
[SUCCESS] Deployed using Spot instances with 40% cost savings and Multi-AZ configuration meeting 99.99% SLA
Our AI agents automatically discover and fix security vulnerabilities using AWS native services. Every deployment is scanned by IAM Access Analyzer and AWS GuardDuty to detect privilege escalation, overly permissive policies, and threat patterns before they become issues.
Automatically detects and fixes overly permissive policies and privilege escalation risks
Real-time threat detection and automated remediation of suspicious activities
AWS CloudTrail integration with real-time anomaly detection and automated response
Intelligent instance selection and autoscaling policies with spot pricing
StackAgent Pro is continuously evolving to meet the demands of modern cloud infrastructure. Our roadmap focuses on deepening AWS integration and enhancing agent capabilities for enterprise-scale deployment.
Native support for AWS specialized inference chips to reduce inference costs by up to 60% while maintaining performance.
Collaborative agent framework for complex cloud operations. Agents will autonomously diagnose issues, recommend fixes, and execute remediation actions.