Overview
AI agents and enterprise applications depend on fast, trustworthy, and governed context to make decisions. Without strong context governance, organizations face increased security risk, inconsistent outputs, compliance exposure, and operational delays across AI workflows.
Wexa is a high-performance context governance platform designed to help enterprises manage, secure, and govern AI context before any agent takes action. Built on Wexa proprietary database technology, the platform delivers low-latency access to governed enterprise context while maintaining sovereignty and infrastructure control.
Wexa enables organizations to deploy AI systems with confidence by centralizing context management, enforcing governance policies, and supporting secure enterprise-scale operations. The platform is optimized for organizations that require fast data processing, strong governance controls, and infrastructure sovereignty for AI-driven workloads.
Highlights
- Govern AI context before agent execution
- High speed proprietary database optimized for AI workloads
- AWS compatible deployment model for scalable enterprise AI operations
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
Pricing
Vendor refund policy
This is a Bring Your Own License (BYOL) product. Refunds for the software license are subject to the terms and conditions agreed upon between the customer and Wexa. Please contact support@wexa.ai for any refund-related requests.
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Delivery details
Wexa Fabric on Amazon EKS (Helm)
- Amazon EKS
- Amazon EKS Anywhere
Helm chart
Helm charts are Kubernetes YAML manifests combined into a single package that can be installed on Kubernetes clusters. The containerized application is deployed on a cluster by running a single Helm install command to install the seller-provided Helm chart.
Version release notes
Patched all the images with r2 security context and helm chart
Additional details
Usage instructions
WEXA FABRIC ON AMAZON EKS - INSTALLATION
Fabric installs into your existing EKS cluster with Helm. Do the steps in order: prerequisites, storage, IAM, license, install, DNS, verify.
STEP 1 - PREREQUISITES
Tools:
- Amazon EKS cluster
- kubectl, Helm v3.19+, AWS CLI v2
- IAM permission to create roles and policies
- Your AWS Account ID
- An S3 bucket for Knowledge Base files
Cluster add-ons:
- OIDC provider enabled (IRSA)
- AWS Load Balancer Controller
- Amazon EBS CSI Driver
- A default StorageClass
- About 160 GiB of persistent storage
Nodes:
- 7x m6i.xlarge or larger for general workloads
- 1x c6i.16xlarge or larger, dedicated to CognoDB
STEP 2 - STORAGE
Skip this if you already have a default StorageClass. Otherwise save the following as storageclass.yaml:
apiVersion: storage.k8s.io/v1 kind: StorageClass metadata: name: gp3 annotations: storageclass.kubernetes.io/is-default-class: "true" provisioner: ebs.csi.aws.com volumeBindingMode: WaitForFirstConsumer allowVolumeExpansion: true reclaimPolicy: Delete parameters: type: gp3 encrypted: "true"
Apply it:
kubectl apply -f storageclass.yaml
STEP 3 - IAM ROLES (IRSA)
Create 4 IRSA roles, one per service account:
-
fabric-license-gate license-manager:CheckoutLicense, CheckInLicense
-
fabric-litellm bedrock:InvokeModel, InvokeModelWithResponseStream, Converse, ConverseStream, ListFoundationModels
-
fabric-data-service secretsmanager:CreateSecret, DescribeSecret, GetSecretValue, PutSecretValue, UpdateSecret, DeleteSecret S3 read/write limited to your Knowledge Base bucket
-
kube-system/aws-load-balancer-controller Standard AWS Load Balancer Controller IAM policy
STEP 4 - LICENSE
Email support@wexa.ai with your AWS Account ID, company name and number of seats. You will receive a Grant ARN and a License ARN.
Accept the grant:
aws license-manager accept-grant --grant-arn <GRANT_ARN> --region us-east-1
Activate it:
aws license-manager create-grant-version --grant-arn <GRANT_ARN> --status ACTIVE --client-token "$(uuidgen)" --region us-east-1
The grant must be ACTIVE before you install.
STEP 5 - INSTALL
Log in to the registry:
aws ecr get-login-password --region us-east-1 | helm registry login --username AWS --password-stdin 709825985650.dkr.ecr.us-east-1.amazonaws.com
Install. Replace <AWS_ACCOUNT_ID>, <LICENSE_ARN>, <KB_BUCKET_NAME> and fabric.yourcompany.com with your values:
helm install fabric oci://709825985650.dkr.ecr.us-east-1.amazonaws.com/wexa-ai/fabric
--version 1.0.7
--namespace fabric --create-namespace
--set ingress.host=fabric.yourcompany.com
--set license.licenseArn="<LICENSE_ARN>"
--set services.license-gate.serviceAccount.annotations."eks.amazonaws.com/role-arn"="arn:aws:iam::<AWS_ACCOUNT_ID>:role/fabric-license-manager-irsa"
--set services.litellm.serviceAccount.annotations."eks.amazonaws.com/role-arn"="arn:aws:iam::<AWS_ACCOUNT_ID>:role/fabric-bedrock-irsa"
--set services.data-service.serviceAccount.annotations."eks.amazonaws.com/role-arn"="arn:aws:iam::<AWS_ACCOUNT_ID>:role/fabric-data-service-secrets-irsa"
--set aws.s3BucketName="<KB_BUCKET_NAME>"
--timeout 15m
STEP 6 - DNS
Get the ALB hostname:
kubectl -n fabric get ingress fabric
Create a DNS record for your ingress host pointing at that ALB.
STEP 7 - VERIFY
kubectl -n fabric get pods
App pods should be Running. Install Jobs showing Completed is normal.
If a pod stays Pending:
kubectl -n fabric describe pod <POD_NAME>
Usual causes: no default StorageClass, EBS CSI Driver missing, not enough node capacity, CognoDB node misconfigured, or IRSA permissions missing.
SUPPORT
Email support@wexa.ai with the output of: kubectl -n fabric get pods helm status fabric -n fabric
Support
Vendor support
Wexa provides comprehensive support for our BYOL (Bring Your Own License) product. Our support team is committed to helping you successfully deploy and operate Wexa in your AWS environment.
SUPPORT CHANNELS: Email: support@wexa.ai
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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