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Multi-Tenant Team Workspaces
Create isolated team environments, invite collaborators with secure tokens, and configure custom rule-based role permissions.
Community Showcase · Release v0.15.0
Engineering work, with an AI-native control plane.
ForgeFlow AI unifies multi-tenant team collaboration, GitHub intelligence, governed AI actions, debugging, progress evidence, and adaptive theming into one engineering workspace.
PROJECT HEALTH
92Optimal ↑
◈ Planner
Multi-tenant roadmap
Multi-tenant roadmap
⌁ Code Reviewer
Diff context ready
Diff context ready
⌘ Debugger
Local lexical RAG
Local lexical RAG
✓ Progress Tracker
Evidence synchronized
Evidence synchronized
INTELLIGENCE FEED
Team invitation acceptedSenior engineer joined with custom permissions.
PR evidence linkedImplementation activity mapped to team roadmap.
Governed action pendingAction proposed: waiting for leader sign-off.
Tri-lingual brief generatedAutomated delivery brief compiled in EN/DE/FA.
Capabilities
One workspace, seven specialist lenses.
The architecture combines project state, team isolation, and repository context so AI assistance stays grounded in the work instead of floating above it.
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Self-Serve User Onboarding
Structured role-aware signup (Student, Professor, Team Lead) with secure session handling and automated database migrations.
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Full Tri-Lingual Parity
Native English, German (DE), and Persian (FA) internationalization with full RTL layout support and localized intelligence briefs.
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Adaptive Theme System
Instant Day/Night toggle, comprehensive settings drawer with System/Light/Dark persistence, and customized UI palettes.
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Repository Intelligence
Bounded lexical repository retrieval, diff-aware review assistance, and debugging recommendations grounded in code context.
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Governed Automation
Side effects are strictly controlled. AI actions follow an explicit propose → approve boundary before any writes execute.
Control model
Propose. Approve. Execute.
Automation is useful only when its authority is legible. ForgeFlow AI separates reasoning from side effects with a governed action lifecycle.
01
Propose
An action is formed with explicit intent and payload instead of mutating project state invisibly.
02
Approve
A human-controlled boundary decides whether the proposal is allowed to become an actual change.
03
Execute
Approved operations use server-side authority, bounded inputs, ownership checks, and auditable results.
Public showcase boundary. This repository intentionally excludes private user/team databases, live production credentials, student submission records, and internal deployment configurations. The public edition documents architecture and provides a runnable, safe subset for the community.
Open-source showcase
Follow ForgeFlow AI as it evolves.
Browse the architecture, feature matrix, security model, contribution guide, and latest release directly on GitHub.