Carify

Carify applies Web3 principles to car trust, replacing biased ratings with a decentralized reputation layer built on user claims, evidence, and transparent signals cutting out the noise in marketing .

Comment

Inspiration

(This is a solo project, building from my own inspo) Buying a car is way more confusing than it should be. Prices are influenced by brand bias, dealership incentives, fake reviews, and vague "trust scores" that don't really explain why a car is considered good or bad. As users and builders, we wanted a way to evaluate cars based on transparent, community-backed signals instead of opaque ratings or centralized platforms.

That idea turned into Carify — a system focused on trust, evidence, and accountability around car reputation.

What it does

Carify is a car reputation and trust platform that allows users to:

  • Search and explore cars without brand-driven bias
  • Submit claims, reviews, and supporting evidence tied to specific vehicles
  • Build a reputation layer around cars using aggregated user contributions
  • See how a car's trust score evolves over time based on verified activity

Instead of a single rating, Carify focuses on why a car is trusted (user provides evidence).

How we built it

We split the project into a clean frontend–backend workflow.

  • Frontend: A simple, fast web interface for searching cars, viewing reputation data, and submitting claims
  • Backend: REST APIs built with Node.js and Express to handle car data, reviews, claims, and evidence uploads
  • Database: MongoDB for flexible schema design around cars, claims, and reputation signals
  • Architecture: Designed around future extensibility for ranking algorithms and aggregation logic

The backend was structured to support future Web3 or decentralized trust extensions, even though the MVP stays lightweight.

Challenges we ran into

  • Designing a reputation system that doesn't collapse into a single meaningless score
  • Handling schema evolution while iterating fast during a hackathon
  • Avoiding over-engineering while still planning for long-term scalability
  • Debugging deployment and environment mismatches under time pressure

A lot of time went into deciding what not to build.

(Also somehow had 2 front-end folders 😅)

Accomplishments that we're proud of

  • A working end-to-end product that actually solves a real trust problem
  • A backend architecture that's clean, readable, and extensible
  • Successfully implementing claims + evidence instead of shallow reviews
  • Keeping the scope realistic while still ambitious

Most importantly: we shipped something usable.

Also gained experience with Solana!

What we learned

  • Trust systems are harder than they look — simplicity matters
  • Clear API contracts save hours of frontend–backend pain
  • Hackathons reward execution more than perfection
  • Designing for transparency changes how you think about data

What's next for Carify

  • Implementing reputation aggregation and ranking logic
  • Adding user credibility weighting over time
  • Improving visualization of trust signals and trends
  • Exploring decentralized identity or on-chain verification for claims
Share this project:

Updates