AGENTIC STAR - AI Agent Platform for AWS
AGENTIC STAR is an AI agent platform for AWS that automates deployment of an integrated environment with Amazon EKS, Amazon RDS for PostgreSQL, vector search, authentication, observability, and LLM routing through LiteLLM with AWS Bedrock support.
- Category
- Application Development
- Registry category
- Software DevelopmentDevOps & CI/CD
- Vendor
- SoftBank Corp.
- Location
- Not disclosed
- Reviews
- Not rated (0 reviews on the listing)
- Listed on
- AWS Marketplace
- Pricing
- 6 plans listed
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What the publisher says
OVERVIEW
AGENTIC STAR is an AI agent platform delivered as an AWS CloudFormation stack. It automates the deployment and configuration of an integrated environment for building, managing, and running AI agents, including Kubernetes infrastructure, data services, authentication, LLM routing, logging, and monitoring.
AGENTIC STAR is designed for platform engineering, ML, and DevOps teams that want to reduce the manual effort required to integrate and operate multiple AI infrastructure components.
Show the rest of the publisher’s description (67 more lines)
WHY AGENTIC STAR
Simplified Infrastructure Integration: Provisions and configures Amazon EKS, databases, vector search, LLM routing, authentication, networking, and observability components through a coordinated deployment.
AWS Integration with LLM Flexibility: Routes inference through LiteLLM with AWS Bedrock support. Integration with other model providers available through LiteLLM is subject to configuration and provider compatibility.
Integrated Operational Capabilities: Includes components for IAM-based access control, VPC-integrated networking, authentication, monitoring, metrics, and logging.
USE CASE EXAMPLE
Example use case: An enterprise knowledge assistant.
A team can deploy AGENTIC STAR and configure an internal support agent that uses company documentation for semantic search and retrieval workflows. Qdrant and PostgreSQL with pgvector provide vector data capabilities, while queries can be routed through AWS Bedrock using LiteLLM.
The Chat UI provides a web interface for employees to interact with the agent. Keycloak supports authentication and team-based access control, while Prometheus, Grafana, Loki, and related monitoring components provide visibility into application and infrastructure health.
KEY FEATURES
Automated Deployment: Provisions Amazon EKS, Amazon RDS for PostgreSQL, Amazon S3 storage, VPC networking, and Kubernetes applications through nested AWS CloudFormation templates
AI-Ready Data Stack: Includes Qdrant and PostgreSQL with pgvector for vector search, embeddings, and retrieval workflows
Chat UI: Provides a web interface for chat, agent configuration, and team management
Integrated Observability: Includes Prometheus, Grafana, Loki, Alloy, and Amazon CloudWatch Container Insights
Enterprise Security Components: Includes IAM roles, VPC-integrated networking, Keycloak authentication, NGINX Ingress, and cert-manager
LLM Routing: Routes inference through LiteLLM with AWS Bedrock support and configurable integration with other compatible model providers
Optional Datadog Integration: Provides an optional integration for application performance monitoring and observability
WHAT GETS DEPLOYED
AWS Infrastructure:
Amazon EKS cluster with system and user node groups
Auto Scaling configuration for EKS node groups
Amazon RDS for PostgreSQL with the pgvector extension and Multi-AZ configuration
Amazon S3 storage for application data and static content
VPC networking with public and private subnets
NAT Gateway and Elastic IP
IAM roles and policies
Bootstrap Amazon EC2 instance for automated Helm installation
Kubernetes Applications and Supporting Components:
Agent Executor
AgenticAI Admin
AgenticAI ExtAPI
Agent Sandbox Controller
Chat
Chat Auth with Keycloak
Keycloak Extensions
Qdrant
kube-prometheus-stack
Prometheus Adapter
Loki
Alloy
Kubernetes Monitoring
AgenticAI Observability
NGINX Ingress
cert-manager
ExtAuth Service
Gate Services
DB Migration
Init Platform
PVC Lifecycle Manager
AgenticAI Datadog
Upgrade Controller
PRICING
This product uses metered pricing through AWS Marketplace. AWS infrastructure costs, including Amazon EKS, Amazon RDS, Amazon EC2, NAT Gateway, and Amazon S3 usage, are billed separately by AWS based on resource consumption.
PREREQUISITES
An AWS account with the IAM permissions required to create the AWS resources used by the product
Sufficient Amazon EC2 vCPU service quotas for the Amazon EKS node groups
Appropriate service quotas for Amazon EKS, Amazon RDS, Amazon VPC, and Amazon EC2
Access to an LLM endpoint, with AWS Bedrock recommended for use through the LiteLLM gateway
EXTERNAL DEPENDENCIES
This product downloads the following external dependencies during deployment:
kubectl from kubernetes.io
Helm from helm.sh
yq from the mikefarah/yq GitHub repository
Helm charts and installer packages from seller-managed object storage
Container images from a seller-managed container registry
SoftBank Corp. manages the availability, security, and integrity of artifacts hosted on SoftBank-managed infrastructure. Third-party dependencies are governed by their respective providers.
GETTING STARTED
To learn more about AGENTIC STAR or request a guided deployment walkthrough, contact SoftBank Corp. through the official inquiry form.
Preview
3 imagesPlans and pricing
6 plans listed
Linked repositories
Unknown
Unknown means this listing does not publish a repository. It is not a statement that the code is closed.
Publisher resources
- Product Video (opens in a new tab)
- aws.amazon.com (opens in a new tab)
- Product Documentation (opens in a new tab)
Sources
- Marketplace listingAWS Marketplace (opens in a new tab)
- Legal linkStandardEula (opens in a new tab)
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