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Asyntra

AI-powered operating system for software development freelancers. Automatically scrapes job listings, classifies them by client using LLM agents, and generates budget and timeline estimates which are surfaced on a live dashboard.

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Image disclaimer: The banner above was generated using an AI image generation tool for presentation purposes only.

Features

  • Automated Job Scraping — Pulls live listings from multiple websites via Firecrawl
  • LLM Job Parsing — Converts raw scraped markdown into structured job objects with category, complexity, urgency, and budget fields
  • Client Inbox & Classification — Groups jobs by client/company, enriches each project with detailed functional and non-functional requirements using an AI agent
  • Invoice Generation — Automatically estimates budget ranges and timelines for every project using a dedicated invoicing agent
  • Gmail Integration — Scans your inbox for inbound freelance opportunities and feeds them through the same pipeline
  • Redis Caching — All three pipeline stages are individually cached in Upstash Redis with a 30-minute TTL to avoid redundant LLM calls
  • Live Dashboard — React frontend with a pipeline view (active projects + invoices) and a leads view (classified companies and requirements)
  • FastAPI Backend — Single /jobs endpoint orchestrates the full scrape → parse → classify → invoice pipeline with structured logging at every stage

Architecture

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Setup

Backend

git clone https://github.com/lahack2k26/Asyntra.git
cd Asyntra
pip install -r requirements.txt
uvicorn main:app --reload --port 8000        # runs on http://localhost:8000

Frontend

cd frontend
npm install
npm run dev   # runs on http://localhost:3000

Environment variables

Variable Description
FIRECRAWL_API_KEY Firecrawl web scraping API
ASI_ONE_API_KEY ASI:1 LLM for all agents
UPSTASH_REDIS_REST_URL Upstash Redis REST endpoint
UPSTASH_REDIS_REST_TOKEN Upstash Redis auth token

About

Stop hunting for freelance work. Asyntra automatically scrapes, ranks, and prices your best opportunities using a 3-stage LLM pipeline, surfaced on a live AI dashboard.

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