Application enablement layer
AI Fabric Framework
Live application data, evidence-grounded retrieval and governed actions for Java and Spring Boot.
- Live data sync
- Governed RAG
- Controlled actions
Open-source portfolio
Products
Build grounded, governed AI behavior in the backend and present it through a reusable application experience.
Two products · Equal portfolio status · Distinct ownership boundaries
Products from the lab
User experience layer
AI Fabric Chat UI
A reusable, framework-neutral chat interface for AI Fabric-enabled applications.
- Web Component
- React
- Arabic and RTL
- Four layouts
Built to work together
Responsibility boundaries
Adopt the layer you need without relocating application authority.
The framework and UI solve different parts of the product surface. Neither replaces identity, authorization, domain policy or business execution.
Responsibility AI Fabric Framework AI Fabric Chat UI
Grounding and retrieval contracts Owns Renders evidence
Action lifecycle contracts Owns Renders proposal and confirmation
Conversation presentation Returns backend state Owns
Identity and authorization Host application Host application
Business execution Host application Host application
Architecture
From application context to user-visible evidence.
- 01 Host application
- 02 AI Fabric Framework
- 03 Backend response contracts
- 04 AI Fabric Chat UI
Related proof
See the products operating in bounded applications.
Each experiment links to source and states what its scenario does and does not demonstrate.
AI Shopping Experience
A shopper explores synthetic products, asks grounded questions and inspects the evidence behind the response.
The health surface reports AI Fabric 0.4.0 and enabled chat, retrieval and data-sync capabilities.
Account Resolver
A user asks for account help, reviews the proposed operation and confirms only after the application exposes validation evidence.
Validation warnings can be shown without silently discarding user-confirmed values.
Live Data Sync
An operator creates, updates and removes synthetic application entities while watching the AI index converge.
Create, update and delete operations have visible indexing state.
Open source
Build with the source in view.
Both products are developed publicly under Apache 2.0, with implementation examples and release history available on GitHub.