As a user, I want all existing scaffold pages (home, login, signup, welcome, dashboard/overview, dashboard/ai-assistant, dashboard/settings) to visually match the mock-design pages exactly. This includes applying the color palette (#1A1D2E background, #2E3447 surface, #F5F7FA text, #06B6D4 cyan accent, #A3A8B8 muted), typography, spacing, and layout structure from all designed pages. Remove any pages not required by the user flows or design specs. This task must be completed independently before any other UI work begins.
As a user, I want to view the Landing page (v2 design) that showcases the azure-workspace product, allows solo developers and freelancers to explore the demo, and leads them to login or sign up. Implement the Living Workspace Garden concept with dynamic growth animations, interactive knowledge graph preview, agent activity visualization (glowing orbs), micro-interactions on hover, and time-based color transitions. Reference the existing Landing (v2) JSX design.
As a user, I want to sign in to azure-workspace via the Login page (v2 design) with email/password authentication. The page serves as the entry point for Solo Developer, Project Manager, Freelancer, Small Business Owner, and Enterprise Team personas. It links to the signup flow and redirects to the Dashboard on success. Implement using the Login (v2) JSX design with the dark theme and cyan accent.
As a user, I want to view the Dashboard page (v1 design) that shows daily briefings summarizing overnight AI agent activity, scheduled run results, active task stats, and predictive insights. It is the first page seen after login for all personas. Supports navigation to Jobs, Workspace, Chat, and Settings. Implement using the Dashboard (v1) JSX design with responsive widgets and glassmorphism styling.
As a user, I want to use the Chat page (v2 design) to type natural language commands for AI agents to execute tasks such as browser automation, data extraction, research, and form filling. The page displays real-time agent activity feeds, GenUI cards (approval, progress, results, error), and live multi-screen browser streaming. Used by Solo Developer, Freelancer, and Small Business Owner personas. Implement using the Chat (v2) JSX design.
As a user, I want to use the Workspace page (v1 design) as the central hub for viewing the interactive knowledge graph, browsing artifacts, reviewing findings, exploring entity relationships, searching entities, viewing timelines, and reviewing insights. Used by all personas. Implement the 3D-feel graph with pulsing connections, node previews on hover, and canvas/timeline tabs. Reference the Workspace (v1) JSX design.
As a user, I want to use the Jobs page (v1 design) to monitor active and scheduled AI agent tasks, view agent activity logs, schedule automated monitoring tasks for recurring workflows, and see real-time status of running jobs. Used by Project Manager, Enterprise Team, and Small Business Owner personas. Implement using the Jobs (v1) JSX design with real-time status indicators and radar-ping alert styling.
As a user, I want to use the Settings page (v1 design) to configure notification preferences, manage user permissions and workspace configurations, and customize workspace behavior. Used by Freelancer (Configure Notifications) and Enterprise Team (Manage Permissions) personas. Implement using the Settings (v1) JSX design with tabbed sections for notifications, permissions, and workspace config.
As a user, I want to use the Export page (v1 design) to download results and reports in multiple formats (PDF, Excel, JSON, PPTX, ZIP with audit trail and SHA-256 manifest). Used by Solo Developer (Download Results), Freelancer (Download Results), Project Manager (Share Report), Small Business Owner (Share Report), and Enterprise Team (Download Audit Report) personas. Implement using the Export (v1) JSX design.
As a user, I want to use the backend API to retrieve daily briefing summaries, agent activity stats, scheduled run results, and real-time workspace metrics for the Dashboard page. Implement FastAPI endpoints: GET /api/dashboard/briefing, GET /api/dashboard/stats, GET /api/dashboard/activity-feed using PostgreSQL workspace tables.
As a user, I want to use the backend AI API to submit natural language commands, receive real-time streamed responses from AI agents, and view execution progress via SSE. Implement FastAPI endpoints: POST /api/chat/command, GET /api/chat/stream/{session_id}, using LangChain for agent orchestration and Litellm for LLM routing across GPT, Claude, and Gemini models.
As a user, I want to use the backend API to retrieve artifacts, entities, relationships, canvas items, and timeline data for the Workspace page. Implement FastAPI endpoints: GET /api/workspace/artifacts, GET /api/workspace/entities, GET /api/workspace/graph, GET /api/workspace/timeline, GET /api/workspace/search with PostgreSQL tsvector full-text search and pgvector similarity search.
As a user, I want to use the backend API to create, monitor, schedule, and cancel AI agent jobs. Implement FastAPI endpoints: GET /api/jobs, POST /api/jobs/schedule, GET /api/jobs/{job_id}/status, DELETE /api/jobs/{job_id}, with real-time status updates via SSE and PostgreSQL intelligence_runs audit trail.
As a user, I want to use the backend API to generate and download export packages in PDF, Excel, PPTX, JSON, and ZIP formats with SHA-256 manifest and audit trail. Implement FastAPI endpoints: POST /api/export/generate, GET /api/export/{export_id}/download supporting all formats.
As a user, I want to use the backend API to read and update notification preferences, user permissions, and workspace configurations. Implement FastAPI endpoints: GET /api/settings, PUT /api/settings/notifications, GET /api/settings/permissions, PUT /api/settings/permissions with role-based access control for admin vs regular users.
As a user, I want the backend AI engine to automatically organize workspace content by detecting patterns across agent runs (e.g., grouping 10 Tesla-related runs into a Tesla project), creating relationship links between related findings, identifying action items from results, and surfacing user preference-based insights. Implement using LangChain agents with PostgreSQL artifact/entity tables.
As a user, I want the backend to build and maintain a temporal knowledge graph using PostgreSQL pgvector, tracking relationships between artifacts, entities, and facts over time. Implement graph construction from agent outputs, relationship scoring, and vector similarity search for the Workspace page's interactive graph visualization.
As a user, I want to see real-time AI agent activity in the Dashboard and Chat pages via a live activity feed showing agent status, discoveries, and progress. Implement Valkey pub/sub → SSE → React pipeline with FastAPI SSE endpoints and Zustand state management on the frontend for zero-latency updates.
As a user, I want all frontend pages (Dashboard, Chat, Workspace, Jobs, Settings, Export) to be fully connected to their backend APIs using React Query for data fetching, Zustand for state management, and optimistic updates for instant-feeling UI. Implement keyboard shortcuts for power users (Linear-style) and ensure full-text search works across 100K+ artifacts.

A self-organizing workspace where AI agents cultivate your knowledge, automate tasks, and grow smarter with every interaction. Watch your ideas bloom into compound intelligence.
Watch your workspace grow. Artifacts connect, AI agents traverse the graph, and knowledge compounds in real time.
A living system that organizes knowledge, learns from every interaction, and grows smarter over time.
Your workspace automatically categorizes and links information based on activity and AI insights. No more manual sorting — everything finds its place naturally, like a garden that tends itself.
Effortless StructureIntelligent agents execute browser automation, research, and data extraction while sharing discoveries in real-time. They work alongside you as first-class collaborators, not just tools.
Always WorkingEvery interaction refines your knowledge graph. The engine accumulates insights across sessions, making subsequent runs smarter and faster — true compounding intelligence.
Ever-GrowingA complete toolkit of intelligent features designed to organize, automate, and amplify your productivity.
Type instructions in plain English and let AI agents execute complex tasks across your entire workspace automatically.
Try commands→Watch AI agents work in real time with live updates on task progress, discoveries, and knowledge graph changes.
View feeds→Instantly search across all artifacts, entities, and relationships in your workspace with intelligent fuzzy matching.
Explore search→Start each day with a curated summary of overnight activity, scheduled runs, and actionable insights from your agents.
See briefings→Export results and reports in PDF, Excel, JSON, and more. Share insights with your team in any format they need.
Export options→Customize real-time alerts for task completions, system events, and important workspace changes that matter to you.
Set up alerts→Tailor layouts, themes, and workflows to match your unique productivity style with flexible configuration options.
Customize now→Visualize and navigate the connections between your artifacts, entities, and AI-discovered relationships interactively.
Explore graph→From solo builders to enterprise teams, azure-workspace adapts to how you work and grows with your ambitions.
Ship faster with organized knowledge
Clarity across every project milestone
Own your data, delight your clients
Automate workflows, grow smarter
Scale securely with advanced controls
AI agents execute tasks, extract data, and share discoveries in real-time — growing smarter with every interaction through compound learning.
Task Execution
AI agents autonomously execute browser automation, scraping, and multi-step workflows in the background while you focus on higher-level thinking.
Research
Agents crawl the web, aggregate sources, and synthesize findings into structured artifacts ready for your review.
Data Extraction
Pull structured data from any source — PDFs, web pages, APIs — and automatically map it into your knowledge graph.
Form Filling
Automate repetitive form submissions across platforms using learned context from previous interactions.
Real-Time Sharing
Every discovery, extraction, and insight is shared to your activity feed the moment it happens — nothing gets lost.
Compound LearningCore
Each agent run refines the knowledge engine. Subsequent tasks become smarter and faster, building on every past interaction.
Every research run, every discovery, every connection builds a living graph of intelligence. Entities, artifacts, and relationships emerge automatically as AI agents work.
Compound knowledge in action. This graph grew automatically from 12 research runs about Tesla. Each run discovered new entities, extracted artifacts, and created relationships — no manual tagging or folder creation required.
Explore Full Graph→From solo developers to enterprise architects, see how azure-workspace transforms the way people work.
Start free and scale as your workspace grows. Every plan includes our self-organizing knowledge engine and AI-powered agents.
Perfect for solo developers exploring AI-powered productivity.
Free forever, no credit card required
Includes
For freelancers and teams who need the full power of the living workspace.
Or $24/mo billed annually
Everything in Free, plus
Scalable, secure, and fully customizable for organizations of any size.
Tailored pricing based on your team size and needs
Everything in Professional, plus
Join thousands of teams using azure-workspace to build a living, self-organizing knowledge system. Let AI agents handle the busywork while your ideas compound into something extraordinary.
No credit card required · Self-hostable · Open source
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