Opportunity Radar

AI-powered opportunity discovery that helps people find grants, careers, training, incentives, and business opportunities before they become urgent, with transparent AI reasoning.

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Opportunity Radar

Inspiration

Every day, people miss life-changing opportunities because they discover them too late.

Grants expire. Training programs close. Hiring slows. Business incentives disappear.

The information exists, but it's scattered across hundreds of websites and difficult to connect to an individual's situation.

I wanted to build an AI assistant that doesn't just answer questions. It actively helps people discover opportunities before they become urgent.

What it does

Opportunity Radar is an AI-powered opportunity discovery platform.

It analyzes a person's goals and surfaces relevant:

  • Grants
  • Business incentives
  • Training programs
  • Career opportunities
  • Local programs
  • Partnerships
  • Income pathways

One of the core principles is transparency.

Every recommendation clearly separates:

Verified Evidence (facts from available sources) AI Inference (reasoned suggestions and predictions)

This helps users understand what is confirmed versus what the AI is estimating.

The platform also generates:

  • Opportunity scores
  • Future outlooks
  • Transition plans
  • Recommended next actions

How I built it

The project was built with a modern TypeScript and React stack and deployed on Vercel.

Major technologies include:

  • React
  • TypeScript
  • Vite
  • Tailwind CSS
  • Remotion
  • GitHub
  • Vercel
  • OpenAI GPT-5.6

I also produced the demo video entirely with an AI-assisted production workflow.

How GPT-5.6 and Codex accelerated development

GPT-5.6 and Codex dramatically accelerated development.

Instead of spending time writing repetitive boilerplate, I focused on product architecture, user experience, transparency, and opportunity scoring while Codex helped implement, refactor, validate, and improve the codebase.

Codex was used throughout development to:

  • Build application features
  • Improve project structure
  • Generate production-ready code
  • Refactor components
  • Validate builds
  • Fix issues quickly
  • Produce the final demo assets

This allowed me to iterate much faster while keeping the focus on solving the real problem.

Challenges

The biggest challenge was balancing intelligent AI recommendations with user trust.

Rather than presenting AI output as fact, Opportunity Radar explicitly distinguishes verified evidence from AI-generated reasoning, helping users make informed decisions with greater confidence.

What's next

Future versions will include:

  • Continuous opportunity monitoring
  • Personalized notifications
  • Collaboration tools
  • Additional opportunity categories
  • Deeper personalization
  • Enterprise integrations

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