Sold by: Compass UOL
Deployed on AWS
AI-powered code analysis and business rule extraction that generates modernization artifacts for enterprise legacy systems, complementing AWS Transform initiatives.
Overview
AI/Cockpit Smart Engineering for AWS Transform Composability
AI/Cockpit Smart Engineering is an enterprise solution that accelerates the understanding, documentation, and modernization of legacy systems. It applies AI-assisted software engineering to analyze source code, extract business rules, identify dependencies, generate technical and functional documentation, and produce engineering artifacts that support AWS Transform modernization initiatives.
HOW IT WORKS
AI/Cockpit Smart Engineering ingests legacy source code and applies AI-driven analysis to produce structured, actionable engineering outputs:
- Code Analysis and Dependency Mapping. Parses legacy codebases to identify dependencies, data flows, and system interconnections.
- Business Rule Extraction. Isolates embedded business logic from source code and surfaces it in human-readable formats.
- Documentation Generation. Produces technical and functional documentation directly from analyzed source code.
- Modernization Artifact Creation. Generates epics, user stories, acceptance criteria, test scenarios, architecture diagrams, and other engineering inputs that support modernization workflows.
- Traceability and Governance. Maintains linkage between legacy code elements and generated artifacts to support enterprise governance and controlled modernization workflows.
Smart Engineering generates the code intelligence, documentation, backlog, and engineering artifacts used as inputs to modernization. Code transformation, testing, remediation, and production validation occur downstream within AWS Transform/ATX modernization workflows or within the customer's target engineering environment. Generated artifacts are intended to accelerate these workflows and should be reviewed and validated within the applicable target environment before production use.
SUPPORTED LANGUAGES AND TECHNOLOGIES
Smart Engineering supports analysis of a broad range of enterprise and legacy technologies, including:
- COBOL, Copybooks, and JCL
- VisualAge
- HLASM and Assembly
- IBM RPG III and RPG IV
- Natural
- Clipper and VB6
- Java
- C and C#
- Python and Go
- TypeScript
- PHP and Ruby
- PL/SQL
- ESQL and IBM ACE
- MuleSoft and DataWeave
- .NET project and solution structures
Additional source code, configuration, markup, database, and project formats can also be ingested as part of application codebase analysis.
KEY BENEFITS
- Accelerate legacy understanding. Convert complex legacy source code into structured engineering knowledge and reduce analysis and documentation effort.
- Extract business rules at scale. Surface embedded business logic and dependencies that would otherwise require extensive manual review.
- Generate modernization artifacts. Produce epics, user stories, acceptance criteria, test scenarios, architecture diagrams, and other engineering inputs that can be reviewed and used by downstream modernization workflows.
- Support enterprise governance. Maintain traceability between legacy code and modernization artifacts to support audit, review, and compliance requirements.
- Complement AWS Transform programs. Add specialized Smart Engineering capabilities for legacy understanding, codebase analysis, requirements generation, test generation, and modernization planning within AWS Transform engagements.
USE CASES
- Large-scale application assessment. Analyze portfolios of legacy applications to prioritize modernization candidates and understand interdependencies across systems.
- Legacy code documentation. Generate comprehensive technical and functional documentation for undocumented or poorly documented codebases.
- Business rule discovery. Extract and catalog business rules embedded in legacy code so they can be preserved and validated during modernization.
- Modernization planning. Produce architecture diagrams, epics, user stories, and other engineering inputs to accelerate modernization planning and downstream execution.
- Software engineering acceleration. Reduce manual effort in application assessment, test scenario creation, requirements gathering, and modernization preparation.
PRICING MODEL
AI/Cockpit Smart Engineering uses a metered pricing model through AWS Marketplace, based on the volume of source code processed by Smart Engineering. See the Pricing tab on this listing for metered dimensions and rates.
GETTING STARTED
Product documentation is available at https://docs.aicockpit.ai/ . To discuss how the product fits your modernization initiative, contact the support team at the email listed in the Support section of this listing. Onboarding guidance and support contact channels are provided during setup.
Custom development, consulting services, manual code remediation, modernization execution, production validation, deployment, and customer-specific integrations are not included in the Smart Engineering product subscription.
Highlights
- AI-assisted code analysis for enterprise legacy systems, identifying dependencies, business logic, application structure, and technical relationships to accelerate system understanding, documentation, and modernization planning.
- Automated business rule extraction and modernization artifact generation, including epics, user stories, acceptance criteria, test scenarios, and architecture diagrams, providing structured engineering inputs for downstream modernization workflows.
- Technical and functional documentation generated directly from source code, with traceability between legacy business logic and modernization artifacts. Outputs are designed to support AWS Transform/ATX initiatives across assessment, planning, code transformation, and validation workflows.
Details
Sold by
Delivery method
Supported services
Delivery option
AI Cockpit Smart Engineering ECS Deployment
AI Cockpit Smart Engineering Helm Deployment
Latest version
Operating system
Linux
Deployed on AWS
New
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Features and programs
Financing for AWS Marketplace purchases
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
Pricing is based on actual usage, with charges varying according to how much you consume. 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.
Dimension | Description | Cost/unit |
|---|---|---|
1 Code Analysis Unit = 1,000 source lines processed by Smart Engineering. | Measures code processed for analysis, documentation, backlog, and modernization support. | $2.81 |
Dimensions summary
You pay based on usage, measured in Code Analysis Units. One unit equals 1,000 source lines of code processed by Smart Engineering. This single dimension covers all processing activities, including code analysis, documentation, backlog support, and modernization. Your cost scales directly with the volume of code you run through the tool. The more source lines you process, the more units you consume. There are no separate tiers or fixed plans. Billing tracks actual code volume, so you pay only for what you process.
Top-of-mind questions for buyers
One Code Analysis Unit equals 1,000 source lines of code processed by Smart Engineering. The tool counts the lines it runs through analysis, documentation, backlog support, or modernization. A file with 2,500 source lines consumes three units, since counting rounds up to the next thousand.
One unit type covers all processing activities. Analyzing legacy code, generating documentation, building backlog items, and proposing modernized versions all draw from the same Code Analysis Unit count. You do not pay separate rates per activity. Cost tracks only the total source lines processed across every function.
Charges apply to each 1,000 source lines the tool processes. Running the same codebase through Smart Engineering again consumes units again for that pass. Cost reflects processing volume, not distinct files. Re-analyzing or re-documenting a system counts as new processing and adds to your unit total.
docs.aicockpit.ai
Helpful?
Vendor refund policy
All fees are non-refundable once usage is metered, delivered, or consumed.
Refunds may be considered only in cases of billing errors, duplicate charges, or service delivery issues confirmed by AI/R Compass UOL.
Usage-based charges are calculated based on metered Code Analysis Units and cannot be refunded after the corresponding code analysis or artifact generation has been executed.
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AI Cockpit Smart Engineering ECS Deployment
Supported services: Learn more
- Amazon ECS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
The model list is read from Amazon Bedrock, so only models the account can invoke are offered. Fixes model ids that Bedrock rejected.
Additional details
Usage instructions
Prerequisites:
- A VPC with two private subnets in different Availability Zones that have outbound internet access (NAT gateway) or VPC endpoints for ECR, S3, Bedrock, CloudWatch Logs, Secrets Manager, License Manager, and AWS Marketplace Metering
- Two subnets for the Application Load Balancer (public subnets if users connect from outside the VPC)
- Access to Amazon Bedrock in the target AWS account
- Three buyer-managed S3 buckets for source, output, and workspace data
- Permission to create CloudFormation stacks with IAM roles
Install:
- Open the CloudFormation template: https://aic-marketplace-public-assets-605656922701.s3.amazonaws.com/aic-modernization/ecs/2026-09-17.2/aic-modernization-ecs.yaml
- Launch it in the CloudFormation console with this quick-create link:
https://console.usvm.9mmj.com/cloudformation/home#/stacks/quickcreate?templateURL=https://aic-marketplace-public-assets-605656922701.s3.amazonaws.com/aic-modernization/ecs/2026-09-17.2/aic-modernization-ecs.yaml&stackName=aic-modernization
Or launch it with the AWS CLI:
aws cloudformation create-stack
--stack-name aic-modernization
--template-url https://aic-marketplace-public-assets-605656922701.s3.amazonaws.com/aic-modernization/ecs/2026-09-17.2/aic-modernization-ecs.yaml
--capabilities CAPABILITY_IAM
--parameters
ParameterKey=VpcId,ParameterValue=<VPC_ID>
ParameterKey=PrivateSubnet1,ParameterValue=<PRIVATE_SUBNET_1>
ParameterKey=PrivateSubnet2,ParameterValue=<PRIVATE_SUBNET_2>
ParameterKey=LoadBalancerSubnet1,ParameterValue=<LB_SUBNET_1>
ParameterKey=LoadBalancerSubnet2,ParameterValue=<LB_SUBNET_2>
ParameterKey=SourceBucket,ParameterValue=<SOURCE_BUCKET>
ParameterKey=OutputBucket,ParameterValue=<OUTPUT_BUCKET>
ParameterKey=WorkspaceBucket,ParameterValue=<WORKSPACE_BUCKET> - When the stack is complete, open the FrontendUrl stack output.
Required configuration:
- Set SourceBucket, OutputBucket, and WorkspaceBucket to buyer-managed S3 buckets
- Add CORS rules to the source bucket that allow the FrontendUrl and ApiUrl origins, the PUT and POST methods, and upload headers
- Set LoadBalancerScheme to internet-facing and AllowedIngressCidr to your client range if users connect from outside the VPC
- For HTTPS, set CertificateArn to an ACM certificate and PublicHostname to its DNS name, then point that name at the LoadBalancerDnsName output
- If needed, override BedrockModelId and BedrockModelIdSmall with supported Bedrock model IDs available in the buyer AWS account
Notes:
- The stack deploys frontend, API, worker, gateway, PostgreSQL, and Valkey as ECS services on AWS Fargate
- PostgreSQL and Valkey data is stored on an encrypted Amazon EFS file system that is retained if the stack is deleted
- To use your own PostgreSQL database, set ExternalDatabaseUrlSecretArn to a Secrets Manager secret holding the database URL
- Database migrations run automatically before the API starts
- For upgrades, update the stack with the template URL of the new version and keep the existing parameter values
Resources
Vendor resources
Support
Vendor support
AI/R Compass UOL provides support for AI/Cockpit Smart Engineering, covering product access, onboarding guidance, configuration questions, usage support, troubleshooting, incident investigation, and clarification of metered usage.
SUPPORT HOURS
Standard support is delivered during business hours, Monday through Friday, excluding local holidays. Support is available through the official contact channels provided during onboarding or defined in the applicable AWS Marketplace agreement.
SUPPORT SCOPE
- Platform availability
- Usage tracking
- Questions about reviewing generated artifacts
- General product operation
OUT OF SCOPE
Not included in standard support unless explicitly contracted through a Private Offer or separate services agreement:
- Execution of code analysis workflows
- Custom development or consulting services
- Manual code remediation
- Migration execution
- Customer-specific integrations
RESOURCES
- Documentation: https://docs.aicockpit.ai/smart-eng-onsite/introduction
CONTACT
- Email: support@aicockpit.ai
For product access, troubleshooting, or usage questions, contact the support team at the address above with a description of the issue and any relevant details to help expedite resolution.
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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