Inspiration
Students and professionals often face life-changing decisions such as choosing between job offers, internships, higher education opportunities, certifications, and career paths. Most people rely on intuition, incomplete information, or generic advice.
DecisionIQ was built to bring transparency and structure to these decisions using AI-powered reasoning.
What It Does
DecisionIQ helps users evaluate complex decisions by analyzing uploaded documents such as resumes, offer letters, and certifications. It extracts relevant information, understands user priorities, performs trade-off analysis, evaluates risks, simulates future outcomes, and provides transparent recommendations.
Key capabilities include:
- Document intelligence and information extraction
- AI-generated follow-up questions
- Weighted decision matrix generation
- Trade-off analysis
- Risk assessment
- Future outcome simulation
- Transparent reasoning trace
- Explainable recommendations
How It Was Built
The platform was developed using Next.js, React, TypeScript, Tailwind CSS, GitHub, and Vercel. AI-assisted development tools were used to accelerate prototyping and implementation.
Challenges
The biggest challenge was designing a transparent reasoning workflow instead of a black-box recommendation engine. The goal was not only to provide recommendations but also explain how and why a decision was reached.
Impact
DecisionIQ enables users to make informed decisions with greater confidence by transforming complex choices into structured, explainable analyses.
Built With
- agents
- ai
- css
- decision
- document
- generative
- intelligence
- learning
- machine
- next.js
- openai
- react
- tailwind
- typescript
- vercel
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