Model-driven generation
Approved architecture and UML models are interpreted by specialist agents and generated into consistent software foundations.
All products
Enterprise Engineering Platform
AO Fabric
Turn enterprise architecture into production-ready software.
The platform
What AO Fabric is
AO Fabric is a model-driven enterprise engineering ecosystem that transforms approved architecture and business models into production-ready software artefacts. It combines automated code generation, APIs, integration, documentation, testing, governance and deployment tooling with specialist AO engineering capability. Traditional software delivery depends heavily on manual interpretation, repeated coding, disconnected documentation and late-stage governance. AO Fabric creates a controlled engineering thread from business requirements and architecture through generated software, integrations, deployment artefacts and operational documentation. Approved source models become a reusable source of truth. Specialist agents interpret those models and generate consistent artefacts, while engineers retain control over the areas that require bespoke business logic, experience design and implementation decisions.
The challenge
What makes this hard today
Fragmented architecture
Inconsistent designs, duplicated patterns and limited architectural governance create long-term complexity.
Slow and manual delivery
Teams repeatedly write foundational code and configuration instead of focusing on differentiated business capability.
Complex integration
Legacy applications, third parties and inconsistent data contracts create fragile interfaces and poor traceability.
Governance added too late
Security, privacy, architecture and compliance controls are often reviewed only after significant implementation effort.
Knowledge loss
Technical knowledge becomes separated from the software and documentation quickly becomes outdated.
Quality and release risk
Manual testing, inconsistent pipelines and uncontrolled changes increase delivery and operational risk.
Costly modernisation
Re-platforming large legacy estates can become slow, disruptive and expensive without reusable models and automation.
Capabilities
How the platform works
Protected customisation
Manually created code is protected from being overwritten when models are regenerated.
Governed integration
REST interfaces, event schemas and data contracts are generated from the same governed models.
Living documentation
Static and dynamic documentation stays tied to the implemented solution.
Embedded governance
Architecture, privacy and security controls are applied while artefacts are created, not only in retrospective review.
Deployment ready
Container packaging, pipeline artefacts and observability foundations are produced alongside the services.
How it works
From start to outcome
Stage 1: Requirements Engineering
Business requirements are refined into clear system capabilities, boundaries, rules and quality requirements.
- Requirements engineering
- Requirements refinement
- Business capability definition
- Domain discovery
- Non-functional requirements
- Security and compliance requirements
Stage 2: Solution Engineering
Architects and analysts define the target solution using governed models and reusable architecture patterns.
- Bounded contexts
- Domain and data models
- Class diagrams
- Microservice definitions
- Endpoint definitions
- Process and micro-flow models
- Pattern catalogue
- UX and interaction requirements
- Infrastructure and DevOps guidelines
Stage 3: Software Engineering
AO Fabric agents interpret the approved models and generate repeatable software and platform artefacts.
- Database scripts
- Database migrations
- Java and Spring Boot services
- REST APIs
- Event schemas
- Business-rule components
- Web and mobile SDKs
- Developer and administration portals
- Unit-test scaffolding
- Documentation
- Deployment pipelines
Stage 4: Controlled Customisation
AO engineers add the bespoke business logic, integrations and user experiences that differentiate the customer platform.
- Custom business logic
- Third-party integrations
- User experience
- Complex algorithms
- Customer-specific controls
- Manual code protection
Manually created code is protected from being overwritten when models are regenerated.
Stage 5: Production Operations
Generated and customised services move through controlled build, deployment, monitoring and support processes.
- Container generation
- Docker packaging
- CI/CD
- Environment configuration
- Cluster deployment
- Portal deployment
- Observability
- Operations and support
- Continuous model evolution
Core components
What the platform is made of
Microservice Engineering
Transforms architecture and UML models into database structures, Java services, REST endpoints and deployment-ready microservice artefacts.
Business Rules
Externalises and manages business rules so that important decisions can evolve independently of core application code.
Event Streaming
Generates governed event schemas and integration components for real-time, asynchronous architectures.
Mobile and Web Engineering
Generates reusable application components, SDKs and portal foundations for web and mobile delivery.
Quality Assurance
Supports repeatable testing through generated test structures and AI-assisted scenario and coverage analysis.
AI-Enabled Engineering
Uses specialised agents and approved AI services to interpret models, create documentation, analyse engineering artefacts and automate repeatable tasks.
Software Governance and Compliance
Embeds governance into the engineering lifecycle through policy enforcement, dependency management, security tracking and audit evidence.
Architecture
A modular platform architecture
01
Foundation Layer
The source of truth for models, data structures, service relationships and system context.
- Model repositories
- Entity definitions
- Data contracts
- Schema automation
- Data protection settings
- Logging and masking rules
02
Rules and Logic Layer
The layer where business behaviour, rules and decision logic are modelled, validated and converted into implementable functions.
- Dynamic rules
- Model interpretation
- Behaviour simulation
- Java and DSL logic
- Decision tables
03
Domain and Event Layer
The industry and integration layer defining domain-specific behaviour and event-driven communication.
- Domain extensions
- Kafka and Avro
- Event schemas
- Integration components
- Analytics hooks
04
Model-Driven Orchestration
The control layer coordinating models, generation pipelines, architecture patterns and lifecycle checkpoints.
- Engineering orchestration
- Model-to-code generation
- CI/CD integration
- Governance by design
- Traceability
05
Observability and Governance
The operational intelligence layer connecting architecture, generated services, runtime behaviour and audit evidence.
- Model observability
- Runtime monitoring
- Compliance intelligence
- Audit trails
- Living documentation
06
Continuous Evolution
The change layer that supports regeneration, testing, deployment and controlled evolution without architectural drift.
- Change pipelines
- Versioned patterns
- Dependency validation
- Security validation
- Continuous regeneration
Platform depth
What the platform provides
Data
- Database schemas
- Migration scripts
- Audit tables
- Multilingual data structures
- Protected-data masking configuration
Services
- Java source code
- Spring Boot microservices
- Hibernate repositories
- RESTful domain services
- Executable API endpoints
Integration
- REST interfaces
- Kafka producers and consumers
- Avro schemas
- Integration adapters
- Event contracts
Experience
- Mobile SDKs
- Web SDKs
- Administration portals
- Developer portals
- Configuration interfaces
Quality
- Unit-test scaffolding
- Test harnesses
- Validation checks
- Coverage-analysis inputs
- Build verification
Documentation
- Static model documentation
- Dynamic-flow documentation
- API documentation
- Payload documentation
- Swagger interfaces
- Developer knowledge content
Operations
- Docker files
- Containerised services
- Deployment configuration
- CI/CD pipeline artefacts
- Observability instrumentation
Outcomes
Business outcomes
- 01Faster delivery of enterprise services and digital capabilities.
- 02Greater architectural consistency across teams and programmes.
- 03Reduced repetition in foundational software engineering.
- 04Clear traceability from models to code, APIs and deployment artefacts.
- 05Earlier enforcement of security, privacy and governance requirements.
- 06Living technical documentation tied to the implemented solution.
- 07Safer evolution of complex platforms over time.
- 08Greater focus by engineers on differentiated business logic.
- 09More consistent build, test and deployment processes.
- 10Improved reuse of approved architecture patterns and components.
Delivered by AO
Value across the organisation
Enterprise Architects
- Architectural agility
- Design, implement and re-platform solutions through reusable, governed models.
- Future adaptability
- Introduce new technologies and evolve platforms while maintaining architectural consistency.
Solution Architects and Senior Developers
- Productivity
- Automate repeatable engineering work and focus attention on complex design and business logic.
- Quality
- Use consistent generated structures, test scaffolding and governance controls.
Information-Security Teams
- Continuous control
- Apply policy, masking, logging and traceability requirements earlier in delivery.
- Vulnerability management
- Improve visibility of third-party libraries, dependencies and security issues.
Business Analysts
- Model verification
- Validate data structures and representative information before full implementation.
- Clear communication
- Use models and generated portals to show stakeholders how requirements are represented.
Chief Financial Officers
- Cost efficiency
- Reduce repetitive engineering effort and improve reuse of approved platform foundations.
- Risk visibility
- Improve traceability, governance and evidence across the delivery lifecycle.
Chief Information Officers
- Operational excellence
- Create more consistent development, integration and deployment processes.
- Strategic capacity
- Allow internal teams to spend more time on differentiated business capability.
Development Teams
- Intelligent automation
- Use specialised agents for repetitive generation, documentation and verification tasks.
- Integration
- Generate consistent interfaces and data contracts across services.
DevSecOps Teams
- Monitoring
- Include operational logging, observability and integration-health foundations.
- Proactive control
- Use audit trails, controlled pipelines and repeatable deployment artefacts.
Where it applies
Typical engagements
- New enterprise platform development
- Legacy-system modernisation
- Core-platform re-engineering
- API and integration programmes
- Event-driven architecture
- Multi-market and multi-tenant platforms
- Regulated financial-services systems
- Enterprise portals
- Platform standardisation
- Large-scale domain decomposition
- Repeatable product-line engineering
- Continuous architecture governance
Delivery model
How it is delivered
Platform technology
Model-driven tooling, generation engines, agents, portals and governance capabilities.
Engineering methodology
AO requirements, architecture, delivery, security, testing and document-control standards.
Reusable patterns
Approved architecture patterns, service foundations, integration components and delivery templates.
Specialist services
AO architects, analysts, software engineers, integration specialists, DevSecOps engineers and support teams.
Proof in practice
Large multi-market enterprise platform
Financial Services
Context
A complex legacy environment required greater delivery speed, architectural consistency, auditability and scalability across distributed teams.
Approach
Model-driven engineering was used to define bounded contexts, generate service foundations, externalise business rules, establish event-driven patterns and embed governance into delivery pipelines.
Where it applies
The programme demonstrated significant automation, improved reuse, reduced manual governance effort and greater delivery capacity.
Customer identities are withheld. Engagements are described at a level agreed for public reference.
Questions
Frequently asked
AO Fabric supports secure and governed software delivery. The platform does not replace customer-specific threat modelling, penetration testing, regulatory interpretation, independent certification or human engineering review.