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We build production-grade FlutterFlow apps that go beyond screens. Our focus is clean component systems, scalable data models, secure integrations, and reliable performance. From MVP to launch and iteration, we deliver apps that are easy to maintain and ready to scale, with full control over API workflows, custom actions, and deployment.
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MessyAPI is a production-ready developer infrastructure platform I built to eliminate repetitive data utility work. It gives developers one API to clean, validate, match, transform, protect, and analyze messy data instead of rebuilding those capabilities for every application.
I designed the platform around real production requirements, including API-key authentication, tenant isolation, usage metering, rate limiting, idempotency, asynchronous jobs, retries, webhooks, observability, and secure data handling.
MessyAPI also includes JavaScript and Python SDKs, OpenAPI, MCP support, CLI tooling, RapidAPI integration, interactive testing, and composable workflows for chaining multiple data operations together.
The goal was simple: turn common data infrastructure developers repeatedly build themselves into one reliable API.
one API for messy data instead of rebuilding it every project is a big win
Problem: Apps need a secure, organized backend to handle users, orders, products and AI features.
Solution: Built a centralized API Gateway (BFF) in n8n Cloud. One webhook handles validation, API key security and rate limiting, then routes to sub-workflows: Users (register/login), Orders (stock check, totals, status), Products (search), and AI (OpenAI chat, recommendations, review summaries). Supabase is the database.
Tools: n8n, Supabase, OpenAI API, Webhooks
Self-initiated demo project.
I'd test authorization separately for each sub-workflow, especially Orders. Does the gateway pass a verified user identity through, or does the Orders workflow check that the caller can access each order?