Trust Data Exchange (TDX)
Overview
The Trust Data Exchange (TDX) is Tythe’s data liquidity layer — a decentralized marketplace for verified, privacy-preserving trust datasets.
TDX transforms static credibility data into a dynamic, tradable resource by allowing verified participants to contribute, license, and monetize their credibility signals at scale.
Each dataset on TDX represents an aggregation of verifiable trust proofs sourced from Tythe’s network — including DISC Scores, Metric Health Factors, and validated behavioral receipts from Trovebook.
Institutions, developers, and AI systems can subscribe to these datasets for use in risk modeling, compliance enforcement, governance analytics, and AI training — without ever compromising the privacy or ownership of the contributors.
Why It Matters
Traditional data exchanges trade information detached from provenance or truth. TDX changes that foundation.
Each dataset is built only from verified contributors meeting specific DISC Score and Metric Health Factor thresholds. Every sample is linked to a Trovebook receipt and anchored to Tythe’s CredibilityRegistry roots, guaranteeing cryptographic authenticity.
TDX delivers verifiable, bias-resistant datasets for:
Financial and risk modeling — using proof-bound trust data instead of unverified credit histories.
Compliance and governance enforcement — automating risk scoring through verified behavioral signals.
AI model training — introducing “trust datasets” to improve model reliability, bias control, and ethical intelligence.
Sustainability and impact analytics — measuring trustworthiness in climate, infrastructure, and ESG systems.
By combining zero-knowledge privacy with transparent verification, TDX makes credibility a liquid digital commodity—standardized, auditable, and continuously priced by trust itself.
How It Works
1. Dataset Templates (Use-Case Families)
TDX organizes its marketplace around Dataset Templates — predefined data families representing core credibility applications. Each template defines schema, logic, and quality metrics.
Compliance Enforcement
Verifiable data on identity, compliance adherence, and rule conformity.
Exchanges, financial regulators, enterprise auditors, money and capital markets, asset managers.
Risk Modeling
Multi-metric credibility data for trust-based risk engines.
Lenders, DeFi platforms, insurers, credit DAOs.
AI Training
Curated behavioral and validation datasets for machine learning systems.
AI developers, model ethics researchers, intelligence labs.
Governance Intelligence
Trust-weighted participation and validation behavior data.
DAOs, institutional governance systems, public sector agencies.
Sustainability Reporting
Verified trust signals from green, infrastructure, or energy domains.
Governments, PoGW/ESG platforms, environmental funds.
Security Assessment
Validation and behavioral proof data for integrity, exploits, or reliability.
Security firms, auditors, infrastructure protocols.
2. Data Tiers
Each Dataset Template is offered in three main tiers, defining scale, cadence, and payout frequency.
All tiers share a unified schema, proof format, and share logic, but differ in sample size and update interval.
Tier I
Mid-scale, fast-refresh datasets ideal for compliance and governance analytics.
≈ 10,000
Weekly
Compliance, Access Control
Tier II
Enterprise-scale datasets balancing metric diversity and refresh efficiency.
≈ 100,000
Bi-weekly / Monthly
Risk, Finance, Governance
Tier III
Large-scale, deep datasets for AI training, sustainability, and behavioral modeling.
≈ 1,000,000
Monthly / Quarterly
AI Training, Sustainability
For smaller datasets (<10,000 samples): explore the TDX Startup Program for early-stage builders and research access.
For larger datasets (>1,000,000 samples): leverage the TDX Enterprise Program for shared-validation deployment and reduced scaling costs.
97% of subscription revenue per dataset is distributed among contributors.
3% is retained by Tythe as the TDX marketplace fee.
Contributors receive payouts in TYT, creating a self-reinforcing credibility economy.
3. Data Licensing Options
1
Anonymized
No ID linkage
1.00×
Generic AI / Low-risk data
2
Non-Anonymized (TRIS ID only)
Traceable ID only
1.25×
Behavioral analytics
3
Non-Anonymized (TRIS & zk-KYH)
Human uniqueness
1.50×
Reputation / Authenticity modeling
4
Non-Anonymized (TRIS & zk-KYC ID)
Identity verified (no AML)
1.75×
Compliance / Regional datasets
5
Non-Anonymized (TRIS & zk-KYC ID + AML)
Full regulatory verification
2.00×
Financial / Institutional systems
Governance and Evolution
New Dataset Templates can be proposed and ratified through Tythe governance.
Future integrations with the GIL Program will allow funded grants to sponsor new dataset classes or bootstrap early contributor rewards.
Dataset performance (volume, validator mix, proof validity) is tracked continuously to ensure market health. Underperforming templates can be deprecated or merged through governance vote.
Privacy and Integrity
All data exchanges occur under zero-knowledge enforcement—no raw personal information is ever exposed.
Proof references are verifiable both off-chain and on-chain through Tythe’s CredibilityRegistry roots.
Every dataset update produces an immutable Dataset Receipt recording epoch, contributors, schema hash, and aggregate metrics.
Composability within Tythe
TDX is fully composable with the broader Tythe ecosystem:
Trovebook: uses verified behavioral receipts and validation proofs as primary data inputs.
DISC Data: aggregates and anonymizes metric-weighted scores for statistical use.
DISC Policies: allows organizations to design proprietary dataset templates aligned with their Validation or Access Policy outcomes.
External Systems: delivers datasets consumable via CSV, JSON, or encrypted API feeds under verified license keys.
Each dataset batch is immutably recorded in Trovebook and anchored on-chain via the CredibilityRegistry, ensuring full proof of origin, non-repudiation, and tamper resistance.
Economic Rationale
TDX transforms credibility into a liquid economic primitive:
Contributors license verified trust data directly for monetization, without intermediaries.
Institutions access high-quality, verifiable trust datasets under programmable privacy.
AI systems train on truthful, bias-minimized, and authenticity-verified data based on real, dynamic human behavior.
By converting proofs of trust into tradeable, permissioned datasets, TDX closes the loop between credibility creation and credibility consumption — forming the foundation of a self-sustaining trust economy.
Last updated
Was this helpful?