EcoLab Overview
EcoLab (version v0.22.0) is an AI-powered econometrics research platform. It is designed to automate and optimize the entire academic research workflow — from initial idea generation to the final published report.
The platform integrates specialized AI agents and over 30 econometrics models to help researchers overcome technical and data bottlenecks.
1. Technology Stack
The EcoLab system is built upon a modern, industry-grade technology stack:
| Component | Integrated Technologies | Purpose |
|---|---|---|
| Frontend | Next.js 14, React 18, TypeScript, Tailwind CSS | Sleek, academic-grade user interface with smooth transitions and optimized user experience (UX). |
| Backend | FastAPI, Python 3.11 | High-performance REST APIs, real-time WebSockets, and AI agent orchestration. |
| Artificial Intelligence | DeepSeek, OpenAI, Gemini, Perplexity, OpenRouter | Multi-LLM provider ecosystem with automatic failover and circuit breaker mechanisms. |
| Database | PostgreSQL 14, Redis 7, Neo4j 5 | User data storage, caching, and complex Knowledge Graph relationships. |
2. Target Audience
EcoLab aims to enhance productivity and research quality for the professional academic community:
- Graduate Students & PhD Candidates: Streamlining the thesis and dissertation preparation process in economics, finance, and social sciences with rigorous scientific standards.
- University Faculty: Assisting in research proposal draft, guiding student research projects, and developing personal academic papers.
- Researchers & Policy Analysts: Assisting research institutes and policy consultants in conducting empirical quantitative analysis with high statistical reliability.
3. 5-Step Research Pipeline
To ensure scientific consistency, EcoLab structures research into a closed loop of 5 steps. Context from previous modules is automatically carried forward to the next:
- Idea Generation: Develop and evaluate preliminary research ideas using keywords or replicate concepts based on existing publications.
- Literature Review: Automate academic searches, identify research gaps, define research objectives, and propose empirical model frameworks.
- Data Collection: Query indicators automatically from public databases (World Bank, FRED, ADB, IMF) or upload local files.
- Modeling: Estimate over 30 econometrics models using Python, R, or Stata execution engines.
- Research Report: Generate draft academic papers formatted in major citation styles (APA7, Chicago, Harvard, etc.) using the advanced STORM writer agent.