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Aetherlab
Enterprise AI model lifecycle control plane
Enterprise AI model lifecycle control plane: inventory, evaluation, deployment approval, monitoring and evidence in one application.
Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v2
Problem
AI pilots multiply across business units without a consistent inventory, evaluation standard or deployment approval, and model risk teams cannot evidence control to auditors or regulators.
Outcome
Every model and AI use case has an owner, an evaluation record, an approval trail and live monitoring, and evidence packs are produced on demand.
Who uses it
- Head of AI
- Model Risk Manager
- AI Platform Team
- Risk Officer
Key capabilities
Model & use-case inventory
IncludedRegister models, LLM use cases, owners, datasets and intended use in a single inventory.
Domain:
modelsStructured evaluations
AI-assistedIncludedDefine evaluation suites and thresholds; record results against each model version.
Domain:
evaluationsDeployment approval
IncludedRoute deployments through model-risk, business and technology approvals with configurable gates.
Domain:
deploymentsProduction monitoring
IncludedTrack drift, performance and incident signals for deployed models.
Domain:
monitorsEvidence packs
AI-assistedIncludedGenerate audit-ready evidence packs per model or per review period.
Domain:
evidencepacksModel-risk tiering
ConfigurableTier models by materiality and apply tier-specific controls.
Typical workflow
Model deployment approval
Trigger: A model version passes evaluation and is proposed for production
Task
Stage 1: Submit version for deployment
Model owner
Automated
Stage 2: Run evaluation suite
AI platform team
AI-assisted
Stage 3: Summarize evaluation results
System
Human checkpoint
Stage 4: Model-risk review
Model risk
Decision
Stage 5: Business approval
Business owner
Automated
Stage 6: Deploy and start monitoring
AI platform team
Task Automated AI-assisted Human checkpoint Decision
About this foundation
Aetherlab gives banks and regulated enterprises one operational place to govern AI models and LLM use cases. Teams register models and datasets, run structured evaluations, route deployments through risk and business approval, monitor production behaviour and generate evidence packs for internal audit and supervisors.
It replaces scattered spreadsheets, notebooks and ticket threads with a governed lifecycle that makes every approval traceable.
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Model deployment approval
Trigger: A model version passes evaluation and is proposed for production
Task
Stage 1: Submit version for deployment
Model owner
Automated
Stage 2: Run evaluation suite
AI platform team
AI-assisted
Stage 3: Summarize evaluation results
System
Human checkpoint
Stage 4: Model-risk review
Model risk
Decision
Stage 5: Business approval
Business owner
Automated
Stage 6: Deploy and start monitoring
AI platform team
Actors
Model owner, Model risk, Business owner, AI platform team
Outputs
- Approved deployment record
- Monitoring configuration
Evidence generated
- Evaluation report
- Approval trail
Exceptions
- Evaluation below threshold returns to owner
Task Automated AI-assisted Human checkpoint Decision
Included ships in the foundation · Configurable is switched or tuned per customer · Extension is customer-specific build scope · Planned is on the roadmap and not available today.
Model & use-case inventory
IncludedRegister models, LLM use cases, owners, datasets and intended use in a single inventory.
Domain:
modelsStructured evaluations
AI-assistedIncludedDefine evaluation suites and thresholds; record results against each model version.
Domain:
evaluationsDeployment approval
IncludedRoute deployments through model-risk, business and technology approvals with configurable gates.
Domain:
deploymentsProduction monitoring
IncludedTrack drift, performance and incident signals for deployed models.
Domain:
monitorsEvidence packs
AI-assistedIncludedGenerate audit-ready evidence packs per model or per review period.
Domain:
evidencepacksModel-risk tiering
ConfigurableTier models by materiality and apply tier-specific controls.
Regulator-specific templates
ExtensionEvidence templates mapped to a specific supervisory guideline.
- Architecture class
- Domain-driven design, OpenAPI-first
- Bounded contexts
- 9
- API-first
- Yes — OpenAPI contracts are authoritative
- Identity
- Enterprise OIDC / SAML via the fazeZERO identity blueprint; tenant-aware role-based access.
- Multi-tenancy
- Tenant-aware
- Service boundaries
- 9 bounded contexts behind one API server.
- Integration approach
- Ports-and-adapters: every external system sits behind an adapter; OpenAPI contracts for inbound APIs.
- Eventing
- Integration events via transactional outbox.
- Storage abstraction
- Repository interfaces; DynamoDB or relational adapters.
- Deployment pattern
- Containerized API + web application; infrastructure as code per cloud profile.
- Architecture version
- 1.0
Approved domain names
- projects
- models
- datasets
- trainingjobs
- evaluations
- deployments
- monitors
- evidencepacks
- identity
- Web Application
- API Server
- Application Services
- Domain / Generated Core
- Adapters
- Customer Systems
Generator source, templates and factory orchestration are proprietary and are not part of this listing.
Reference Adapter: shipped and tested · Previously Integrated: delivered before · Standard API Pattern: integrates via a documented pattern · Customer-Specific: built in your implementation.
Identity
| Integration | Status | Direction | Method |
|---|---|---|---|
| Microsoft Entra ID | Reference Adapter | bidirectional | OIDC |
AI / Model
| Integration | Status | Direction | Method |
|---|---|---|---|
| Azure OpenAI / model endpoints | Standard API Pattern | bidirectional | REST API |
Data
| Integration | Status | Direction | Method |
|---|---|---|---|
| Data platform (Snowflake, Databricks) | Standard API Pattern | bidirectional | REST API |
Observability
| Integration | Status | Direction | Method |
|---|---|---|---|
| Observability (OpenTelemetry) | Reference Adapter | outbound | OTLP |
Ticketing
| Integration | Status | Direction | Method |
|---|---|---|---|
| ServiceNow | Customer-Specific | bidirectional | REST API |
Deployment
- Deployment models
- Customer Cloud, Customer VPC/VNet
- Cloud profiles
- Azure Profile, AWS Profile
- Containerized
- Yes
- Regions
- GCC, SAUDI ARABIA, UAE, EU
Cloud profiles describe approved deployment patterns. They are not formal marketplace certifications.
Azure Profile
- compute
- Azure Container Apps / AKS
- data
- Azure Cosmos DB or PostgreSQL
- identity
- Entra ID
- AI / model
- Azure OpenAI
- observability
- Azure Monitor
- secrets
- Key Vault
- CI/CD
- GitHub Actions
AWS Profile
- compute
- ECS Fargate / EKS
- data
- DynamoDB
- identity
- Cognito or enterprise OIDC
- AI / model
- Amazon Bedrock
- observability
- CloudWatch
- secrets
- Secrets Manager
- CI/CD
- GitHub Actions
Data handling
- Stores customer data
- Yes
- Data leaves customer environment
- Configurable
- Uses external AI provider
- Configurable
- Sends logs externally
- No
- PII expected
- Determined during customer configuration
- Data-residency support
- Yes
- Subprocessors required
- Determined during customer configuration
Identity & access
- Authentication
- OIDC, Entra ID, SAML
- Authorization
- Role-Based, Tenant-Aware
- Source availability
- Proprietary
Support
- Implementation
- Delivered by fazeZERO or a certified partner during the Solution Definition and AI Production Sprints.
- Production support
- Production support available under a separate support agreement.
- Contact
- support@fazezero.com
Badges
Deployment-Ready Foundation
Application has passed the defined fazeZERO scaffold, build and testing baseline.
Customer-specific integration, security, configuration, hardening and acceptance remain part of implementation.
Issued 23 Sept 2026
fazeZERO Verified
Listing metadata and published technical claims have been reviewed by fazeZERO.
Issued 23 Sept 2026
Evidence shows that this listing represents real engineering. Internal metrics are only published when fazeZERO has approved them for publication.
Build
Automated tests
Deployment validation
| Measure | Value | Status | Verified |
|---|---|---|---|
| Build verified | — | Verified | 15 Sept 2026 |
| Automated tests | — | Verified | 15 Sept 2026 |
| Deployment validation | — | Verified | 15 Sept 2026 |
| API operations | 142 | Verified | 15 Sept 2026 |
| Schemas | 96 | Verified | 15 Sept 2026 |
| Test suites | 18 | Verified | 15 Sept 2026 |
| Bounded contexts | 9 | Verified | 15 Sept 2026 |
- Last verification
- 15 Sept 2026
- Release
- 1.0.0
- Architecture version
- 1.0
- Listing metadata version
- 2
- Last published
- 23 Sept 2026