Welcome to Fabric AI

The enterprise platform for SDLC compression through intelligent AI agents, RAG-powered document generation, and durable workflow automation.

Fabric AI is an enterprise-grade platform designed to revolutionize how software teams work. By combining intelligent AI agents, Retrieval-Augmented Generation (RAG), and durable workflow automation, Fabric compresses the entire Software Development Lifecycle (SDLC) from weeks to days.

What is Fabric AI?

Fabric AI is a comprehensive platform that helps development teams:

Generate Documents Instantly — Create PRDs, technical specs, architecture docs, and more using AI agents that understand your codebase and past work
Automate Repetitive Tasks — Let AI agents handle routine work like creating Jira tickets, posting updates, and syncing information across tools
Unlock Your Knowledge Base — Process and search through PDFs, Confluence pages, code repositories, and legacy documentation using RAG
Orchestrate Complex Workflows — Chain multiple agents together for multi-step tasks with built-in error recovery and human approval workflows

Key Features at a Glance

AI Agents

Pre-built and custom agents that can generate documents, execute API calls, and automate workflows

RAG System

Upload documents and let AI agents access relevant context from your knowledge base

Prompt Library

Versioned, reusable prompts with template variables for consistent AI interactions

MCP Integration

Connect to external tools like GitHub, Jira, Slack, and more using the Model Context Protocol

Durable Workflows

Multi-Tenancy

Enterprise-grade isolation with organizations, teams, and role-based access control

Who is Fabric AI For?

Product Managers

Transform rough ideas into detailed PRDs in minutes instead of days
Ensure consistency across all product documentation
Automatically generate user stories with acceptance criteria

Developers

Access instant context from past projects and documentation
Generate technical specs and architecture documents
Spend less time on documentation, more time on code

Engineering Managers

Improve team velocity without sacrificing quality
Enable better knowledge sharing across teams
Get real-time visibility into workflow progress

Enterprise Leaders

Accelerate time-to-market for new features
Reduce risk from knowledge loss when employees leave
Demonstrate compliance with documented processes

Quick Start

Get started with Fabric AI in under 5 minutes:

Create your account at fabric.pro using email, magic link, or social login.

Configure AI Provider

Navigate to Settings → AI Gateway and add your API key for OpenAI, Anthropic, or other supported providers.

Create Your First Agent

Go to Agents → Create Agent and choose from pre-built templates like Document Generator or create a custom agent.

Start a Conversation

Select your agent and start chatting! Ask it to generate a document, answer questions about your codebase, or automate a task.

Ready to dive deeper? Continue to Getting Started for a comprehensive guide.

Architecture Overview

Fabric AI is built on a modern, scalable architecture:

┌─────────────────────────────────────────────────────────────────┐
│                         Fabric AI Platform                       │
├─────────────────────────────────────────────────────────────────┤
│  Frontend (Next.js 16)                                          │
│  ├── React 19 + Tailwind CSS + Shadcn UI                       │
│  ├── CopilotKit for AI-powered UI                              │
│  └── TipTap for rich document editing                          │
├─────────────────────────────────────────────────────────────────┤
│  Backend API (Hono + oRPC)                                      │
│  ├── Type-safe RPC with automatic OpenAPI generation           │
│  ├── Better Auth for authentication                            │
│  └── Multi-tenant data isolation                               │
├─────────────────────────────────────────────────────────────────┤
│  AI Layer                                                       │
│  ├── Vercel AI SDK for LLM integration                         │
│  ├── LangGraph agents (TypeScript/Python)                      │
│  └── MCP for external tool integration                         │
├─────────────────────────────────────────────────────────────────┤
│  Data Layer                                                     │
│  ├── PostgreSQL (primary database)                             │
│  ├── Qdrant (vector database for RAG)                          │
│  └── S3/MinIO (file storage)                                   │
├─────────────────────────────────────────────────────────────────┤
│  Orchestration                                                  │
│  ├── Temporal (durable workflow execution)                     │
│  └── .NET Aspire (polyglot service orchestration)              │
└─────────────────────────────────────────────────────────────────┘