FRED-Flow: Enterprise Macroeconomic Data Engine - Sell Project
Listed February 22, 2026
About FRED-Flow: Enterprise Macroeconomic Data Engine
Turn chaotic FRED data into clean, analysis-ready datasets in seconds.
Test the Live Showcase: https://fred-flow.vercel.app/ Explore the API Docs (Swagger): https://fred-flow-api.onrender.com/docs Turn 816,000+ raw Federal Reserve indicators into clean, aligned, analysis-ready datasets — in seconds. FRED-Flow is a full-stack ETL pipeline and analytics dashboard purpose-built for economists, quants, data scientists, and fintech teams. It connects directly to the Federal Reserve Economic Data (FRED) API, solves the painful problem of multi-frequency time-series alignment, and delivers pristine datasets to your browser in three clicks. The Problem It Solves: Anyone who has worked with FRED data knows the pain: Misaligned frequencies (merging Daily FEDFUNDS with Quarterly GDP). Aggressive API rate limits (HTTP 429) that break scripts mid-extraction. Disparate scales (plotting Trillions vs. Percentages). Format juggling (CSV, Parquet, SQLite). FRED-Flow solves all of these in a single, production-grade product. Enterprise Readiness & Due Diligence: It's built to pass technical audits: Test Coverage (88%): Automated pytest suite covering alignment logic and edge cases. Developer Handoff: Fully-typed OpenAPI schema ready for Postman / Insomnia import. OSS Compliance: Exhaustive OSSLICENSES.md generated to guarantee strict Open Source Initiative compliance (no viral/GPL licenses). Clean Infrastructure: Multi-stage Docker Compose setups for both Dev and Prod. Tech Stack: Frontend: Next.js 14 (App Router), React 18, Tailwind CSS, Shadcn UI Backend: Python 3.11+, FastAPI, WebSockets (for real-time progress) Data Engine: Pandas, PyArrow (Time-series alignment via Outer Join) What You Get (Included in Sale): 100% Full Source Code & IP rights. Production-Ready Docker Configs. Automated Test Suite & CI/CD pipeline ready. Built-in "Demo Mode" for your own showcases. Perfect to skip 40-60+ hours of data engineering setup. Grab the repository, run the container, and start extracting. 💡 Ready to deploy your own macroeconomic data platform? Purchase directly, or send me a DM if you have any technical questions before buying!
Next step: <p>The project is built as a modular microservice architecture, allowing for rapid expansion in several high-growth directions:</p><p><br></p><p><strong>1. SaaS Monetization:</strong> Integrate a payment gateway (Stripe/LemonSqueezy) to transform FRED-Flow into a subscription-based macroeconomic research terminal.</p><p><strong>2. AI & LLM Integration:</strong> Leverage the clean data pipeline to feed Large Language Models for automated market sentiment analysis and executive summaries.</p><p><strong>3. Multi-Source Expansion:</strong> Extend the ETL engine to ingest data from the World Bank, IMF, or ECB using the existing time-series alignment logic.</p><p><strong>4. Automated Alerting:</strong> Build a notification engine (Email/Slack/Discord) that triggers when specific indicators (e.g., Yield Curve inversion, CPI spikes) hit thresholds.</p><p><strong>5. Advanced Analytics:</strong> Add predictive modules using the existing Pandas/PyArrow stack to forecast trends based on historical FRED data.</p>
For sale
Asking price: $399 USD
What's included
Source code, All related design work
Full Intellectual Property (IP) rights, 88% test coverage suite (Pytest), complete Docker/Docker-Compose production configurations, GitHub Actions CI/CD workflows, and full OpenAPI/Swagger documentation.
Reason for selling
The codebase is technically complete, stable, and production-ready. I am currently shifting my full attention to a new development project, so I've decided to sell this asset to someone who can focus on its commercial growth while skipping the initial 40-60 hours of engineering setup.
Project metrics
Average Monthly Revenue: Pre-revenue
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