Building AI-Powered Analytics: Lessons from Plotsalot 📊
Natural language interfaces transforming data analysis. Learn how we integrated Claude, GPT, and Azure OpenAI to turn plain English into insights and visualizations.
Building AI-Powered Analytics: Lessons from Plotsalot 📊
Natural language interfaces are transforming how users interact with data. Here's what we learned building Plotsalot, an AI-powered analytics platform.
The Vision
Enable non-technical users to analyze complex datasets using plain English, automatically generating visualizations and insights.
Technical Stack
- Frontend: Next.js with TypeScript
- AI Integration: Claude, ChatGPT, Azure OpenAI
- Code Execution: Sandboxed CodeSandbox environments
- Database: PostgreSQL with Prisma ORM
- Storage: AWS S3 for data and GCP for compute
Architecture Highlights
1. Multi-Model AI Strategy
We integrated multiple AI models to ensure high-quality code generation across different data analysis scenarios.
2. Secure Code Execution
Running user-generated Python/R code required isolated sandbox environments with strict resource limits.
3. Real-Time Collaboration
WebSocket-based live updates enable teams to collaborate on dashboards in real-time.
Challenges We Solved
Challenge: AI-generated code could be inefficient or incorrect Solution: Implemented validation layers and optimization passes before execution
Challenge: Users needed to refresh data regularly Solution: Built auto-refresh scheduling with configurable intervals
Impact
Users reduced analysis time from hours to seconds while maintaining professional-grade output quality.
AI + data visualization = democratized analytics.