Corridor GGX on AWS combines governed AI delivery with the elasticity and security of Amazon Web Services — streamline AI governance, run real-time data pipelines, and manage model compliance from a unified platform.
Amazon S3 and Amazon Redshift give GGX the durable foundation it needs to power governed AI, from raw inputs and trace data to evaluation results and reporting.
Securely store datasets, prompts, outputs, and review artifacts in durable object storage with lifecycle controls, encryption, and fine-grained access policies.
Analyze governed AI telemetry, evaluation scores, and business outcomes in a warehouse built for high-scale reporting, auditability, and operational visibility.
Key features
Amazon Bedrock and Amazon SageMaker plug into GGX for governed experimentation, evaluation, and production delivery of LLM-powered workflows.
Route governed prompts and evaluations through managed foundation models while keeping policy checks, traceability, and release controls in one workflow.
Operationalize model development, offline evaluation, and workflow automation with managed ML tooling that fits regulated deployment environments.
Key features
Amazon RDS and Amazon EC2 keep GGX deployments resilient and elastic while fitting existing enterprise networking, scaling, and operational controls.
Run managed relational databases for platform state, governance metadata, and workflow history with backups, patching, and multi-AZ durability built in.
Scale API workers, evaluation runners, and supporting services with flexible compute capacity that can be isolated and tuned to match enterprise requirements.
Key features
AWS security controls help GGX keep sensitive AI workloads encrypted, access-controlled, and aligned with internal risk and compliance standards.
Protect data in transit and at rest with AWS-native encryption controls, including KMS-backed key management for sensitive workflow assets.
Use role-based access, scoped permissions, and federated identity patterns to enforce least-privilege access across teams, environments, and release flows.
Key features
Bring GGX into your AWS environment with Bedrock, SageMaker, S3, RDS, and the governance layer your business, risk, and engineering teams need.
