Learn with credibility

Tythe enables AI Agents to refine performance through feedback-integrated learning loops, where every validated action informs future DISC recalibrations.

Learning is driven by the Agent’s verified behavioral traces and by Decision Relays submitted from trusted validators or partner organizations.

This framework ensures that AI systems evolve through objective trust data — not subjective fine-tuning.

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Key Components

• Decision Relays:Decision Relays

  Structured attestations from validators or integrator platforms that confirm or contest Agent actions, feeding verified feedback into the DISC Engine.

• Trovebook Feedback Mapping

  Each validated trace and its corresponding outcome are cross-referenced in the Agent’s Trovebook to refine metric weighting and improve decision logic.

• Metric Health Calibration

  DISC Metrics — including Governance, Technical, Compliance, and Security — dynamically update based on validated reliability, enabling continuous trust-driven learning.

Agents become self-correcting credibility systems, learning directly from verifiable trust signals and producing continuously improving, bias-resistant behavior.

Tythe transforms model improvement into a trust-anchored process. Every behavioral adjustment stems from verified data, ensuring that AI learning remains accountable, auditable, and bias-resistant.

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FAQs — Learn with Credibility

How do AI Agents receive feedback? Through Decision Relays and verified Trovebook outcomes, which update DISC metrics based on confirmed behavior and validator reports.

Can learning occur autonomously? Yes, but all learning-based updates must originate from verifiable inputs — no self-attestation is allowed.

How often are DISC metrics recalibrated? Continuously, but global recalibration checkpoints occur weekly through Tythe’s off-chain computation layer and root hash updates.

Can human Registrants override an Agent’s learning data? No. Registrants maintain accountability, but all metric updates depend solely on validated records, ensuring trust integrity.

What happens if a Decision Relay disputes an Agent’s action? Disputes are logged as counter-signals and reflected in the Agent’s DISC calculation, lowering associated metric health until resolved.

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