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.
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.
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:
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.
Highlights
Automate the deployment of an integrated AI agent environment through AWS CloudFormation, including Amazon EKS, Amazon RDS for PostgreSQL, storage, networking, authentication, and observability components.
Support semantic search and retrieval-augmented generation workflows using Qdrant and PostgreSQL with pgvector, with LLM routing through LiteLLM and AWS Bedrock.
Operate the platform with IAM roles, VPC-integrated networking, Keycloak authentication, NGINX Ingress, cert-manager, Prometheus, Grafana, Loki, and Amazon CloudWatch Container Insights.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on a fixed subscription cost and actual usage of the product. You pay the same amount each billing period for access, plus an additional amount according to how much you consume. The fixed subscription cost is prorated, so you're only charged for the number of days you've been subscribed. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
You pay by the hour based on the compute instance you run this platform on. The five options are different AWS EC2 instance types, not feature tiers. Each carries its own hourly rate tied to that instance's compute and memory profile. The t3.medium and t3.large are burstable general-purpose instances. The m5.large, m6i.large, and m7i.large are general-purpose instances from different processor generations. You choose the instance that fits your workload and deploy it to your own environment. Your total cost scales with how many hours you keep the instance running.
Top-of-mind questions for buyers
What do the hourly rates cover, and are AWS infrastructure costs separate?
Each hourly rate is the software charge for running AGENTIC STAR on that EC2 instance type. AWS charges for the underlying compute, storage, and network separately. Your invoice combines both. The instance type you pick sets the software rate and the compute and memory you receive.
Am I charged when an instance is stopped or paused?
Software charges meter running instance-hours. A fully stopped instance stops accruing the hourly software fee. Stopped instances may still incur AWS storage fees for attached volumes, but those are separate from the software charge. You control cost by controlling how long each instance runs.
Can I run more than one instance, and how does that affect my bill?
You can deploy the platform to your own cluster and run multiple instances. Each running instance meters its own hourly software charge based on its type. Your total software cost is the sum of all running instances multiplied by their hours. You can mix instance types across your deployment.
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AGENTIC STAR AMI with CloudFormation (EKS Full Stack)
This delivery option uses nested AWS CloudFormation templates to provision the full AGENTIC STAR platform. The entry-point template (main-template.yaml) orchestrates all nested stacks: VPC with NAT Gateway, Amazon EKS cluster with managed node groups, RDS PostgreSQL 16.6 with Multi-AZ HA, S3 buckets, and an ephemeral Setup Helper EC2 instance that installs 23 Kubernetes microservices via Helm.
A placeholder Marketplace EC2 instance (t3.medium) is provisioned in the public subnet to satisfy AWS Marketplace AMI-based product requirements. This instance does not run any application workload.
External dependencies downloaded at deployment time include Helm binaries and charts from seller-managed object storage, and container images from a seller-managed container registry.
CloudFormation Template (CFT)
AWS CloudFormation templates are JSON or YAML-formatted text files that simplify provisioning and management on AWS. The templates describe the service or application architecture you want to deploy, and AWS CloudFormation uses those templates to provision and configure the required services (such as Amazon EC2 instances or Amazon RDS DB instances). The deployed application and associated resources are called a "stack."
Version release notes
Version 2.7.0 release of AGENTIC STAR on AWS Marketplace.
This release upgrades the bundled Helm installer to version 2.7.0, delivering new platform features through the microservices layer. The AWS CloudFormation templates were updated to right-size the default infrastructure: the RDS instance class and Multi-AZ setting are now parameterized with cost-optimized defaults, application pods now access S3 via IAM Roles for Service Accounts (IRSA), and public subnets were expanded to two Availability Zones to remove the single-AZ constraint on the load balancer.
Key changes in this release:
Moderation & governance: added BAN management (admin UI and list / unban APIs)
Admin usability: strengthened CSV import validation and added failure summaries for bulk user registration
Chat UI: added Mini DevTools to the HTML preview, with numerous UI/UX and multilingual fixes
Security hardening: strengthened verification across authentication / input validation / error responses, updated dependencies across multiple services, and enforced encrypted SMTP connections
Platform reliability: improved mail delivery (retry and graceful shutdown), stabilized streaming API responses for long-running generations, and made database migrations safer and idempotent
Operations: unified autoscaling to CPU / Memory metrics, corrected metrics collection settings, and added drift prevention to PVC lifecycle management
Breaking change: removed the legacy fallback authentication provider (authentication paths are now unified)
All existing components from v2.6.0 (EKS with System/User node groups, RDS PostgreSQL 16.10 with pgvector, Qdrant, Chat UI with Keycloak, Prometheus/Grafana/Loki/Alloy observability, NGINX Ingress, cert-manager, AWS Bedrock integration, optional Datadog APM) remain included.
Additional details
Usage instructions
Template components
CloudFormation template
Usage instructions
LAUNCH INSTRUCTIONS
Subscribe to AGENTIC STAR on AWS Marketplace and click "Continue to Configuration".
Select "CloudFormation" as the delivery method, choose your AWS Region, and click "Continue to Launch".
Click "Launch CloudFormation"
the AWS CloudFormation console opens with main-template.yaml pre-loaded.
Fill in the required parameters:
Stack name: choose a unique name (e.g., agentic-star-prod)
ImageId: pre-filled by AWS Marketplace - do not change
EKS node instance types and scaling limits (default: m5.2xlarge, min 2 nodes each group)
RDS instance class and credentials (default identifier: marketplace-db)
Admin email and password for the platform
Primary language (default: ja)
Acknowledge that CloudFormation will create IAM resources.
Click "Create stack". Deployment takes approximately 20~30 minutes.
POST-DEPLOYMENT SETUP
After the stack reaches CREATE_COMPLETE:
Retrieve the EKS cluster name from the CloudFormation Outputs tab.
Run the kubectl config command shown in Outputs to authenticate with the cluster.
Verify all 23 microservices are running: kubectl get pods -A
Access the Chat UI at the URL shown in Outputs.
Configure your LLM provider through the LiteLLM multiLLM gateway (e.g., AWS Bedrock region) via the platform admin panel.
Configure Keycloak with your identity provider if required.
For full documentation, refer to the product User Guide.
SoftBank Corp. provides support for AGENTIC STAR on AWS through the official inquiry form.
Support Scope:
Assistance with AWS Marketplace deployment and AWS CloudFormation launch issues
Guidance for initial configuration and post-deployment setup
Documentation for platform administration and operation
Support for product updates and security-related notices
Troubleshooting for Kubernetes application health and connectivity
Guidance on AWS service quotas relevant to Amazon EKS and Amazon RDS resources
How to Get Help:
For deployment issues, initial configuration questions, operational questions, and other product support inquiries, contact SoftBank Corp. using the official inquiry form.
Sizing Guidance:
AGENTIC STAR requires sufficient vCPU service quotas for the Amazon EKS node groups. Ensure that the AWS account has appropriate service quotas for Amazon EKS, Amazon RDS, Amazon VPC, and Amazon EC2 before deployment. Contact support for assistance with capacity planning and service quota requirements.
For support inquiries, please contact SoftBank Corp. using the following form:
https://www.softbank.jp/biz/contact-us/demand/ai/agentic-star-inquiry/
AWS infrastructure support
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