Application-owned
Identity, policy, domain data and execution stay with the host application.
Independent open-source engineering
Loom AI Labs is the project and brand home for open-source products, runnable engineering proof and implementation-linked research into dependable AI-enabled software.
Maintained by Mahmoud Ashraf Algammal with open-source contributors
Mission
The work focuses on the space between a model API and a dependable product: trusted application context, current data, retrieval evidence, governed actions, visible limitations and reusable user experience.
Loom AI Labs does not treat prompts as a substitute for identity, authorization, source-of-truth data or business execution.
Engineering principles
Identity, policy, domain data and execution stay with the host application.
Context, evidence, clarification and actions cross typed, inspectable boundaries.
Live demos and public implementation support claims; limitations remain visible.
Teams can adopt one capability without relocating their whole application.
Products and runnable proof link back to the implementation they describe.
Prototype, evidence and maturity terms match what public artifacts establish.
One connected body of work
Reusable open-source software with a supported public integration surface.
Bounded applications that make one technical capability inspectable.
Engineering investigations linking questions, implementations and limitations.
Maintainer identity
Loom AI Labs is independently maintained. Contributions are reviewed against the same application-boundary, evidence and source-linking principles used across the public work.
Open-source model
AI Fabric Framework and AI Fabric Chat UI are released under Apache 2.0. Issues and pull requests belong in the relevant public repository, close to code and verification.
Contribution path
Bring an issue, an integration gap or a bounded experiment with enough context for another engineer to inspect it.