Sinpoura AI - A Unified

Sinpoura AI - A Unified Workspace for Multiple AI Models

One workspace. Multiple AI models. Organized conversations.

Sinpoura AI is a modern multi-model AI chat application designed to bring AI conversations, saved discussions, and model integrations into one clean, productive workspace.

Instead of building around a single AI provider, Sinpoura uses a structured multi-provider architecture that connects different language models through one consistent application experience.

Users can create an account, start conversations, organize chat history, configure AI providers, and continue working from a responsive interface.

What the Platform Offers

Multi-Model AI Chat: Connect with supported AI providers, including OpenAI and Anthropic.

Persistent Conversations: Create, retrieve, manage, and delete saved chat threads.

Personal Workspace: A dedicated conversation sidebar and organized chat experience.

Bring Your Own Key (BYOK): Allow users to configure their own supported AI provider credentials.

Quick Prompts: Ready-to-use prompts for writing, studying, debugging, summarizing, and more.

Model Configuration: Manage provider settings and model preferences.

Secure Authentication: Registration, credentials-based sign-in, and protected chat access.

Responsive Experience: Interfaces designed for desktop, tablet, and mobile.

Personalization: Light, dark, and system appearance modes.

Behind the Product

Sinpoura uses xoin-js as its structured multi-provider LLM integration layer.

The application uses server-side chat handling, conversation persistence, input validation, and provider configuration to keep the chat experience organized and extensible.

It also includes browser-based BYOK configuration. User-provided API keys are kept in browser local storage and sent with chat requests; they are not persisted in MongoDB.

Search & Sharing Foundations

The application includes structured page metadata, Open Graph and Twitter images, JSON-LD WebApplication data, sitemap and robots configuration, and public-route SEO foundations.

My Contribution

I developed the application experience and its supporting architecture, including the chat workspace, authentication, conversation management, multi-provider AI integration, and responsive user interface.

The result: A functional multi-model AI chat application and an extensible foundation for building customized AI assistants, internal AI tools, and conversational products.

Project focus: AI Chat Application · Multi-LLM Integration · OpenAI · Anthropic · AI Workspace · Next.js Application · MongoDB · BYOK · Conversational AI