MediScoreX: —Streaming Health Data into Smart Contracts for Trustless Underwriting

Hyperion HyperHack Ideathon
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Project Name

MediScoreX
A Real-Time AI Health Credit Score for Web3 Risk & Access

Problem Statement

In DeFi and Web3 health finance, underwriters, DAOs, and health insurers lack reliable access to real-time, personalized health data. This leads to inefficient credit decisions, coverage gaps, and exclusion of underserved patients with little medical documentation. There’s no transparent system for quantifying health risk across digital identities.

Solution Overview

MediScoreX introduces an AI-native, onchain health credit scoring system that analyzes wearable and medical claim data in real time. Users connect their devices, generate a health score, and share it securely with DAOs or lenders via token-gated access. By combining Hyperion onchain agents, Bolt.new low-code front-end, and Alith’s human-readable AI explanation layer, MediScoreX makes health data usable, understandable, and verifiable in Web3 underwriting.

Project Description

MediScoreX is a decentralized health scoring protocol that empowers individuals to generate dynamic, verifiable health risk scores from wearable data and insurance claims. The flow is simple: users connect data sources through a Bolt.new front end, which calls a Hyperion agent that computes a health score based on defined clinical vectors (e.g., heart rate, sleep, activity level). The result is logged onchain and can be optionally explained by Alith, an AI co-agent that translates raw data into meaningful insights (e.g., “Your low sleep quality reduced your score by 15 points”).

Scores can be token-gated for access by health DAOs, lenders, or employers, creating a new primitive for DeFi-health intersection. The system also introduces a gamified layer where users can earn rewards for improving health behaviors and sharing scores securely.

Users benefit from:

Transparent and personalized health scoring Control over who accesses their health risk data Incentives to improve lifestyle and unlock coverage or lending opportunities

MediScoreX is not just a healthtech tool—it’s a new AI + DeFi primitive for equitable risk assessment, with massive potential for impact in underbanked and underserved populations.

Community Engagement Features :white_check_mark: Testable Features / Tasks:
Connect your wearable or submit health data: +10 pts
Generate your first health score: +15 pts
Ask Alith to explain your score: +5 pts
Share your score with an insurer DAO: +20 pts
Mint your “Health Score NFT”: +10 pts

:video_game: Gamification System: Points tracked in a Leaderboard UI (built in Bolt.new)
NFT Badges for early users, “Top Scorers”, and “Data Completers” DAO referral rewards: users earn tokens for inviting DAOs to onboard
:chart_increasing: Why It Works:

Gamifying health scores encourages curiosity, consistency, and competition. It turns health improvement into a social game while simultaneously providing DAOs with a stream of qualified, risk-profiled leads.

Getting Involved
We welcome contributors across these areas:

Health-focused DAOs seeking to test or underwrite users
Solidity/Hyperion devs to audit or optimize agent code
AI/ML engineers to expand the scoring model
Designers and Bolt builders to improve the user interface
Public health advocates to help with outreach and onboarding.

15 Likes
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Incredible concept bringing real-world health metrics into Web3 with privacy, agency, and game mechanics is a huge unlock. :clap:

Quick question: How do you plan to ensure fairness in scoring across different demographics and health baselines?

4 Likes
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Hello @Okeytx , How are you?

How does MediScoreX ensure verifiability and authenticity of wearable or medical data before generating a health score?

Is there a zero-knowledge proof (ZKP) or privacy-preserving mechanism for score sharing, especially in sensitive underwriting scenarios?

5 Likes
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Thanks, Han! Great question.

We ensure fairness by normalizing inputs based on demographics like age and gender, using diverse training datasets, and providing transparent explanations through Alith. We also monitor for bias with a fairness audit layer and continuously refine the model with expert feedback.

2 Likes
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Hi @priyankg3, thanks for the great questions!

MediScoreX ensures data authenticity by requiring users to connect via OAuth-secured APIs (for wearables) and issuer-attested uploads (for medical claims), all tied to their Web3 wallet signature.

For privacy, we use token-gated access for scores and are integrating zero-knowledge proofs (ZKPs) so users can prove eligibility (e.g., “low risk”) without revealing raw data—perfect for sensitive DeFi underwriting scenarios.

Happy to share more if you’d like a deeper dive!
Okechukwu Obasi, Founder, MediScoreX

2 Likes
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Thanks for the explanation, Okechukwu! :raising_hands:

Would love to follow your progress—keep up the great work! :fire:

3 Likes
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Appreciate the detailed answer!
It’s great to see fairness being approached so systematically especially the combination of normalization, transparency, and ongoing audits. Curious to learn more about how the audit layer operates in practice. Is it automated, or does it rely heavily on human review?