Saigely
A real-time AI chat platform built with Next.js, GraphQL, WebSockets, and OpenAI.
Saigely is an AI chat platform that brings together authentication, real-time conversation streaming, persistent chat history, and GraphQL-backed data access in a single Next.js application. The goal is to explore how a modern chat product can stay responsive, organized, and maintainable without splitting core product concerns across separate services.
Why I Built It
Saigely started as an exploration of how far a unified Next.js runtime could go when paired with modern AI and real-time infrastructure. A lot of chat applications spread authentication, persistence, API logic, and streaming behavior across multiple systems. That can work, but it also adds coordination overhead and makes iteration harder.
I wanted to build a product that treated those concerns as part of one cohesive experience instead of separate problems. The result is a workspace-focused chat platform that is intentionally structured for growth, but still small enough to stay understandable while the product is evolving.
Key Features
- Real-time AI response streaming over WebSockets
- GraphQL API layer for chat, workspace, and user data
- Better Auth for GitHub and Google sign-in flows
- MongoDB persistence for conversations and user data
- Workspace-oriented UI for browsing and resuming chats
- Settings and account controls built for future expansion
- Responsive interface designed for both desktop and mobile layouts
Interface Flow
Saigely is designed around the idea that users should be able to move from sign-in to conversation without friction.
- Login and workspace entry are kept lightweight
- Conversations are organized so active chats are easy to resume
- The main chat area stays focused on the current response stream
- Settings are separated from the core chat flow so the interface stays uncluttered
The current UI is intentionally simple while the product foundation is still being shaped, but the structure is already aimed at a more complete workspace experience.
System Architecture
Saigely combines several moving pieces into one application layer:
- Next.js App Router for rendering and server logic
- GraphQL Yoga for the API surface
- Better Auth for session handling and provider sign-in
- WebSockets for live AI streaming
- MongoDB for persistent storage
- OpenAI for the conversational model layer
The architecture is built to keep the product modular without making the codebase feel fragmented. That balance matters for an app like this, where chat state, identity, and generated output all need to stay in sync.
Lessons Learned
Working on Saigely has been a useful exercise in balancing product scope with technical structure. Real-time AI features are easy to make flashy, but much harder to make predictable and maintainable. The biggest lesson so far has been that the experience only feels good when the underlying data flow stays clear.
The project also reinforced the value of separating concerns early. Authentication, persistence, API design, and response streaming all need to work together, but they should not blur into one another. Keeping those boundaries explicit makes the app easier to extend as the feature set grows.
Future Development
Planned work includes:
- Conversation export and sharing
- Workspace collaboration features
- Smarter conversation organization and search
- Usage analytics and reporting
- Expanded AI workflow tools
- More polished onboarding and account settings