Introduction & Problem

Problem

The Problem We're Solving

Distributed teams juggle chat, whiteboards, and docs across multiple tools.

Fragmented Collaboration Tools

Teams constantly switch between multiple disconnected applications

💬

Chat App

📝

Whiteboard

🤖

AI Assistant

📓

Notes

↔️Context switching breaks flow↔️

Fragmented workflow

Context constantly switches between chat, whiteboards, docs, and notes—ideas get lost and momentum breaks.

No in‑context AI

AI is often a separate tab. Teams can't ask questions, cite sources, or summarize in the exact place collaboration happens.

Real‑time sync pain

Presence, cursors, and concurrent edits are hard to get right—latency and conflicts degrade trust in the tool.

Solution & Features

Solution

The Solution

EchoBoard unifies key collaboration and productivity features into one seamless, real‑time environment. It provides chat, AI assistance, whiteboarding, and personal journaling — all synced instantly, so teams stay in flow and ideas stay connected.

AI‑powered collaboration right where you work
Single tool replacing 3–5 separate apps
Real‑time sync with zero context switching

EchoBoard - Unified Workspace

One platform that brings everything together

✨All-in-one collaboration platform✨

Key Features

Core Capabilities

Unified Platform Architecture

All features seamlessly integrated in one interface

💬

Real-time Chat

Instant messaging with AI assistance

📝

Interactive Whiteboards

Multi-user drawing and collaboration

🤖

AI-Powered Assistance

Context-aware responses and citations

📓

Personal Journaling

Rich text editing with search

🔄Real-time synchronization across all features🔄

Collaboration

Multi‑user rooms with role‑based permissions
Real‑time chat with AI assistance
Interactive whiteboards with live collaboration

AI‑Powered

Context‑aware responses
Web search with inline citations
Voice‑to‑text transcription

Productivity

Personal journaling with rich text editing
Search and tagging across all content
Export and backup capabilities

Tech & Design

Sections 5–6

Technical Architecture & UI/UX Design

Built and designed solo — from systems architecture to interface details.

Technology Stack

Modern, scalable architecture built with cutting-edge tools

Frontend

Next.js 15 + React 19

TypeScript 5

Tailwind CSS 4

Backend

DB

PostgreSQL

Clerk Auth

⚡

Supabase

AI & Real-time

AI

GPT-4o

🔍

Tavily Search

📝

tldraw

5. Technical Architecture

Frontend

Next.js 15 (App Router) + React 19 with TypeScript 5 and Tailwind CSS 4. Streaming SSR, server actions, and code‑splitting for speed.

Framework: Next.js 15 (App Router), React 19 concurrent features
Language: TypeScript 5 with strict configuration
Styling: Tailwind CSS 4, OKLCH color system, custom design tokens
Performance: Streaming SSR, image & font optimization, route‑level code splitting

Backend

Supabase + PostgreSQL with Row Level Security and real‑time subscriptions. Server components fetch data securely.

Database: PostgreSQL (Supabase) with RLS and indexed queries
Auth: Clerk + Google OAuth with role‑based access
Realtime: Supabase Realtime + WebSockets for presence/cursors
SSR: Supabase SSR helpers for secure server‑side rendering

AI & Intelligence

GPT‑4o powers chat, summarization, and guidance. Tavily Core supports web search with inline citations. Voice input via speech‑to‑text.

Model: OpenAI GPT‑4o with streamed token‑by‑token UI
Search: Tavily Core for citations and source popovers
Voice: Real‑time speech‑to‑text for hands‑free input
Context: Conversation memory scoped to room and user role

Real‑time

tldraw for whiteboards with multi‑cursor presence and conflict‑free updates. Optimistic UI and background sync.

Whiteboard: tldraw integration with persistent storage
Presence: Live cursors, typing indicators, and room status
Streaming: NDJSON streaming for AI responses
Offline: Optimistic updates and background sync

6. UI/UX Design System

Design Principles

Clean, accessible, and performant user experience

🎨

Minimal Design

Clean surfaces with generous white space

♿

Accessible First

WCAG compliant, keyboard-first flows

⚡

Performance

Streaming SSR and optimized loading

🌙

Dark Mode Ready

OKLCH tokens for consistent theming

Design Philosophy

Minimal, calm surfaces with generous white space
Accessible by default (WCAG), keyboard‑first flows
Motion used sparingly to guide attention
Dark mode ready via OKLCH tokens

Component Architecture

Primitives: Radix UI patterns; headless, accessible building blocks
Variants: Class Variance Authority for scaleable component states
Motion: Framer Motion micro‑interactions (enter/exit, press)
Tokens: Spacing, radii, type scale, and color mapped to Tailwind

Theming & Tokens

Color: OKLCH palettes for consistent contrast across themes
Type: Variable fonts with optical sizing for crisp rendering
Density: Comfortable defaults with compact variants for data‑dense views

Up next

7. Database & Data Model · 8. Real‑time Collaboration

Continue

Data & Real-time

Sections 7–8

Database & Data Model · Real‑time Collaboration

Solo Project — I designed the schema, wrote policies, and wired realtime.

Database Architecture

PostgreSQL with Row Level Security and real-time subscriptions

Core Tables

👥

profiles

User profiles & metadata

🏠

rooms

Collaborative spaces

💬

messages

Chat with AI citations

Security & Permissions

🔒

Row Level Security

Granular access control

👑

Role-Based Access

OWNER/EDITOR/VIEWER roles

⚡

Real-time Sync

WebSocket subscriptions

7. Database & Data Model

PostgreSQL on Supabase with strict RLS. Entities are room‑scoped where applicable and keyed for fast timelines.

profiles

User profiles, display names, and metadata

rooms

Collaborative spaces with visibility (private/public)

memberships

User ↔ room roles & permissions (OWNER/EDITOR/VIEWER)

messages

Chat messages with optional AI citations

journals

Personal notebooks (per‑user)

journal_entries

Rich text entries with tags & timestamps

room_invites

Email‑based invitations with token expiry

notifications

Event notifications with read state

RBAC & Constraints

Roles stored in memberships; enforced in policies and app
Foreign keys with ON DELETE CASCADE for clean teardown
Indexed queries for messages(room_id, created_at) and entries(journal_id, created_at)

ER Overview (simplified)

rooms

id • owner_id • visibility

memberships

room_id • user_id • role

messages

room_id • author_id • created_at

(Foreign keys with ON DELETE CASCADE; indexes on timeline columns.)

Real-time Collaboration Architecture

Multi-user synchronization with conflict resolution

Presence & Cursors

👤

Live Presence

See who's online

🖱️

Multi-cursor

Real-time cursor tracking

Whiteboard Sync

📝

tldraw Integration

Multi-user drawing

🔄

Conflict Resolution

Last-writer-wins strategy

AI Streaming

🤖

NDJSON Streaming

Token-by-token responses

⚡

Optimistic UI

Instant feedback

8. Real‑time Collaboration

Realtime is powered by Supabase Realtime + WebSockets. Presence and cursors are ephemeral; persistent content is stored in Postgres. tldraw is wired to a room‑scoped store with conflict‑aware updates.

Presence & Typing

See who’s online, where their cursor is, and who’s typing

Live Whiteboards

Multi‑user drawing via tldraw; diff‑based synchronization

Streaming AI

NDJSON token streaming renders responses progressively

Optimistic UI

Mutations apply instantly, reconcile on ack; background sync

Conflict Handling

Room‑scoped locks and last‑writer‑wins for lightweight cases

Performance Considerations

Message timelines indexed; pagination by created_at
Connection pooling; client subscriptions batched per room
Lightweight payloads for presence; avoid writing ephemeral state to DB

Up next

9. Performance & Optimization · 10. Development Workflow

Continue

Outcomes & Learnings

Sections 12–13

Outcome & Impact · Reflection & Learnings

Solo project — delivery from architecture to UI polish.

Project Impact Overview

Measurable improvements in team collaboration and productivity

-40%

Fewer Context Switches

Less tool switching reported in pilot sessions

+25%

Faster Decisions

Time to consensus during whiteboard sessions

<2min

Setup Time

From invite to first collaborative action

12. Outcome / Impact

EchoBoard reduces tool‑switching and keeps teams in flow by unifying chat, AI, whiteboards, and journaling in one real‑time surface.

−40%

Fewer Switches

less context switching reported in pilot sessions

+25%

Faster Decisions

time to consensus during whiteboard sessions

< 2 min

Setup Time

from invite to first collaborative action

Qualitative Wins

AI answers in‑context with citations, so the team trusts the output
Whiteboards + chat side‑by‑side capture decisions where they happen
Personal journals reduce meeting follow‑ups and capturable knowledge loss

Tool Consolidation

EchoBoard can replace or reduce reliance on:

Chat app
Whiteboard app
Personal notes app
Lightweight task tracker

Development Journey

Key learnings and challenges overcome during development

Challenges Faced

⚖️

Consistency vs UX

Balancing conflict resolution with smooth UI

🧠

AI Context Boundaries

Room-scoped memory management

What Worked Well

⚡

Streaming SSR

Responsive, calm user experience

🧩

CVA Variants

Tidy component state management

Future Iterations

📊

Audit Logging

Granular tracking for enterprise

🎬

Session Replay

Replayable whiteboard sessions

13. Reflection & Learnings

Key Challenges

Realtime consistency vs. UX smoothness
Balancing conflict resolution with optimistic UI required scoped locks and pragmatic LWW rules for drawings/messages.
AI context boundaries
Room‑scoped memory and explicit citations improved trust while avoiding cross‑room leakage.
Design tokens at scale
OKLCH tokens simplified dark mode contrast, but demanded careful mapping to Tailwind for consistency.

What Worked

Streaming SSR + NDJSON created a responsive, calm feel
CVA variants kept component states tidy and predictable
Schema first: modeling memberships/roles early avoided policy churn

Next Iterations

Granular audit log for enterprise rooms
Replayable whiteboard sessions with time‑scrub
Inline tasks with due‑dates extracted from chat via AI