Human API

Connecting People, Not Data

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Human API — Connecting People, Not Data

What Inspired Me

I was inspired by how many people feel disconnected despite living in highly connected digital worlds. Social media often measures interaction through metrics, likes, or follower counts, rather than fostering genuine human connection. I wanted to build something that encourages people to meet, collaborate, and share skills or interests in real life, without relying on AI or complex algorithms.

The idea was to create a “Human API” — a simple platform that connects people based on energy, mood, or interests rather than data or machine learning models.

What I Learned

Building Human API taught me several important lessons:

  • Even simple rules can create meaningful connections. You don’t need AI to match people effectively; careful design of input fields and filters works surprisingly well.
  • UX matters more than complexity. A clean interface encourages users to engage rather than feel overwhelmed.
  • Privacy and trust are crucial. Users feel safer when interactions are opt-in and data is minimal.
  • Designing human-centered software often requires balancing simplicity and flexibility, so that users can define what “match” means to them.

I also learned practical web development skills in integrating front-end interactivity with a backend database and live matching logic.

How I Built the Project

Human API was built as a web application with a lightweight and hackathon-friendly tech stack:

Frontend

  • React / Next.js for an interactive interface
  • Tailwind CSS for styling
  • Optional: Mapbox API to display nearby users

Backend

  • Node.js + Express (or Python + FastAPI)
  • Stores user profiles, interests, and availability
  • Implements a simple matching function without AI

Matching Logic

The matching works with a rule-based system, for example:

[ \text{Match} = \begin{cases} \text{True} & \text{if } |E_A - E_B| \le 1 \text{ and } \text{shared_interests} \ge 1 \ \text{False} & \text{otherwise} \end{cases} ]

Where (E_A) and (E_B) represent the energy level or mood of two users.

Features

  1. User Profiles: name, bio, interests, and energy level
  2. Quick Match: shows compatible users nearby or online
  3. Chat / Meet Links: in-app messaging or external platform integration
  4. Filters: optional, for skills, location, or activity

Challenges I Faced

  1. Balancing simplicity and usefulness: Initially, I tried to create too many filters and fields, which made the platform confusing. I had to simplify while keeping meaningful matching criteria.
  2. Real-time matching: For a hackathon MVP, I needed matching to happen instantly. Implementing an efficient in-memory filtering system solved this without a database query delay.
  3. Privacy concerns: I wanted to allow users to see nearby people without exposing exact location. I solved this by using rough geolocation or optional location sharing.
  4. User engagement: Without AI or content recommendations, keeping users interested was a challenge. I focused on emphasizing skill swaps and shared activities to make the platform inherently useful.

Closing Thoughts

Human API demonstrates that technology can foster authentic human connection without relying on AI or algorithms. By focusing on energy, mood, and shared interests, the platform encourages people to meet, collaborate, and share in a meaningful way.

Even with simple rules and minimal data, it is possible to create interactions that are trustworthy, impactful, and genuinely human.

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