In Enterprise GRC, accuracy is the difference between true automation and administrative burden. 

Most "AI for GRC" tools rely on generic Large Language Models (LLMs) wrapped in a chat interface. While these models summarize text well, they struggle with the highly specific demands of compliance. They hallucinate details, miss critical control failures, or flag false positives because they lack deep domain context. For an enterprise, "80% accurate" isn’t an efficiency gain, but a liability requiring 100% manual review.

1. Purpose-Built GRC Models: Building Domain-Specific Expertise

At Zania, accuracy is a structural requirement. We don’t rely on standard models to guess your compliance posture. Instead, we train agents on your organization’s methodologies and frameworks, using GRC data created in-house by our experts.

This approach scales your intellectual property: agents evaluate risk using your distinct criteria, producing output aligned with how senior professionals actually work. By training on dense, expert-created GRC datasets and your organization’s testing methodologies, our agents understand not just what a “control” is, but how you test it.

2. The Quality Scorecard: Measuring What Matters

Unlike general-purpose AI platforms, Zania evaluates every agent’s output with a rigorous Quality Score framework built for enterprise risk and compliance.

Accuracy – The Core of Trust

• Recall: Did the agent miss relevant facts from policies, evidence, or interviews?

• Precision: Did it introduce incorrect statements, hallucinations, or assumptions?

Relevance – Aligned to Actual Controls

• Relevance-to-Control: Is the response tied directly to the control’s intent?

• Specificity: Are recommendations granular, actionable, and evidence-based?

Language Quality – Clear, Consistent, Repeatable

• Tone: Professional, neutral, globally consistent

• Succinctness: No over-explanation, no ambiguity, no filler

Together, these measures eliminate false positives, false negatives, and ungrounded reasoning, producing outputs that internal teams, clients, and auditors can review without clarification cycles.

3. Explainability as a Control

Accuracy alone is insufficient if it cannot be defended in an audit. Zania agents are fully explainable: every assessment includes source citations and confidence scores, providing a full provenance trail. CISOs and partners can verify the "why" behind every "what," transforming the AI “black box” into a defensible system of record.

The New Standard

The future of GRC isn’t about summarizing text quickly; it’s about reliably automating risk decisions. By engineering for precision, recall, relevance, and explainability, Zania delivers automation that speeds compliance and withstands scrutiny.