What AI Model Hub is built to do
Expose an AI operations console for provider coverage, local-runtime status, RAG inventory, executions, usage, and release evidence.
AI Model Hub
AI provider, runtime, RAG, execution, usage, readiness, and release-evidence visibility.
Data & AI
FAIS Hub Product
Purpose and problem
A focused product for a defined operating job.
Expose an AI operations console for provider coverage, local-runtime status, RAG inventory, executions, usage, and release evidence.
The operational gap it resolves
Platform operators need a single read model for AI service readiness, security boundaries, recovery plans, and recent activity before wider runtime control is introduced.
Core capabilities
Capabilities designed around the product boundary.
Provider coverage
Runtime and RAG status
Executions and usage
Release evidence
Use cases
Where teams put AI Model Hub to work.
Designed for: AI platform operators and application teams
Review cloud and private provider coverage
Inspect local model runtime and RAG collection status
Track executions, daily usage, readiness, release evidence, backup, rollback, and support-bundle data
Platforms, protocols, and technology
Built for the environments that industrial teams already operate.
The exact deployment profile is selected during discovery and validated against the target equipment, network, security, and lifecycle requirements.
WebRESTSQLiteCloud-provider metadataLocal-runtime metadataRAG collection metadataBlazor ServerASP.NET Core.NET 10
Platforms, protocols, and technology
Protocols and technology ecosystem
Choose the adapters and services for your equipment and deployment profile.
Databases (1)
Web and communication (2)
.NET
REST API
Logos identify their respective technologies or vendors. Trademarks belong to their owners; no endorsement or certification is implied.
Product composition
A clear architecture from source to operational outcome.
- 01
Inputs and boundary
Blazor operational views
- 02
Core product services
Snapshot-oriented dashboard API and shared persistence foundation
- 03
Experience and outcomes
Readiness, security, recovery, and support evidence endpoints
Product advantages
Why teams choose the FAIS product approach.
Central AI estate visibility
Explicit operational readiness evidence
Consistent usage and execution review
Plan the next step
Evaluate AI Model Hub for your operation.
Share the equipment, workflow, data, security, and deployment constraints. FAIS will help define a focused discovery or pilot path.