How LedgerAI Works

A deterministic system for product-level AI compliance.

Core System

The Complete Traceability Chain

LedgerAI establishes a four-step chain from legal text to documented proof. Each step is explicit, traceable, and auditable.

01

Regulation

Legal text that applies to your product based on jurisdiction, use case, and risk classification.

02

Obligation

Specific requirement extracted from the regulation that your product must satisfy.

03

Control

Technical or procedural implementation that satisfies the obligation.

04

Evidence

Documented proof that the control exists and operates as intended.

Step 1: Regulation

A regulation is a body of law that may apply to your AI product. The EU AI Act, US sectoral frameworks, South African governance requirements-these are regulations.

LedgerAI maintains current versions of applicable regulations across all three jurisdictions. When a regulation changes, the system flags affected products and obligations.

Example: The EU AI Act applies to your chatbot product because it operates in EU markets and processes personal data.

Step 2: Obligation

An obligation is a specific requirement within a regulation that your product must satisfy. Obligations include article references, applicability conditions, and severity classifications.

LedgerAI determines which obligations apply to each product based on:

  • Jurisdiction (where the product operates)
  • Use case (what the product does)
  • Risk level (determined by regulatory frameworks)
  • Data types processed
Example: EU AI Act Article 13 requires transparency obligations for your chatbot. This becomes a tracked obligation in LedgerAI.

Step 3: Control

A control is the technical or procedural implementation that satisfies an obligation. Controls can be code, processes, documentation, or oversight mechanisms.

Engineering teams define controls. Legal teams verify that controls satisfy the mapped obligations. Both work from the same data model.

Example: To satisfy the transparency obligation, you implement a control: "Display AI-generated content notice in chatbot UI." This control is linked directly to the Article 13 obligation.

Step 4: Evidence

Evidence is documented proof that a control exists and operates as intended. Evidence can be code commits, screenshots, policy documents, test results, or audit logs.

LedgerAI tracks evidence items with version control, verification status, and timestamps. When auditors ask, "Prove this control works," you have documented answers.

Example: Evidence for the transparency control includes: a screenshot of the UI notice, the relevant code commit, and QA test results confirming the notice displays correctly.

The Advantage

Why Traceability Matters

When a regulator asks, "How does your product satisfy Article X?"-you don't search through spreadsheets. You follow the chain: Regulation → Obligation → Control → Evidence.

Most compliance tools offer scoring systems or generic checklists. These provide no traceability between legal requirements and engineering implementations.

LedgerAI makes every connection explicit. Legal can see which controls satisfy which obligations. Engineering can see which evidence proves which controls. Auditors can verify the entire chain.

This is not compliance theater. This is systematic accountability.

See the system in action.