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Tim Zinin
Tim Zinin

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I Built an Autonomous AI Agent to Hunt Opportunities in Saudi Arabia's $40B AI Market

Most people hear "Saudi Arabia is the next big market" and nod. I heard it three times from banking friends in one month and decided to automate the research.

The Opportunity

Saudi Arabia is investing $40 billion in AI by 2030. Vision 2030 launched HUMAIN, SDAIA, NEOM. Companies are hiring AI architects, multi-agent engineers, consultants.

The Problem

Tracking opportunities manually is impossible. Jobs appear on LinkedIn, Bayt.com, GulfTalent, corporate sites. Contract news is scattered across dozens of sources.

The Solution: Saudi AI Opportunity Hunter

An autonomous agent that monitors the Saudi AI ecosystem 24/7:

  • Jobs loop (every 6h): 12 search queries across job boards
  • News loop (every 12h): 10 queries for contracts, tenders, investments
  • LLM scoring: Groq Llama 3.3 70B scores each finding (0-100 relevance)
  • Telegram alerts: Instant notification for scores > 70
  • Daily digest: Summary at 09:03

First Run Results

  • 115 jobs collected
  • Max relevance score: 90/100
  • 6 parallel asyncio loops

Architecture

saudi-hunter/
main.py (278 lines) | collectors.py (280) | scorer.py (170)
notifier.py (230) | db/schema.sql (6 tables, 9 indexes)
requirements.txt (3 deps: httpx, aiosqlite, python-dotenv)
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One Docker container. Less than 128MB RAM. Less than 5% CPU.

Stack: Python 3.12, asyncio, Firecrawl API, Groq (free tier: 100K tokens/day), SQLite, Telegram Bot API.

The Key Insight

This agent is not Saudi-specific. Swap the search queries and profile, and you get monitoring for any market: UAE, Singapore, Latin America.

Next: Automated Outreach (Phase 2)

Phase 2 adds automatic pitch generation, email drafts via Gmail API, response detection, and follow-up automation.

Full architecture breakdown: https://timzinin.com/saudi-hunter/?utm_source=devto&utm_medium=social&utm_campaign=saudi_hunter&utm_content=sh_01

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