Quantify & Mitigate AI Workflow Risks Before Deployment
An original, research-backed risk classification engine designed for Small and Medium Enterprises. Evaluate data privacy exposure, hallucination impact, governance authority, copyright liabilities, and human-in-the-loop necessity across any operational AI task.
Why SME AI Governance Demands Structured Evaluation
Small and medium-sized businesses face unique operational trade-offs when integrating Generative AI into customer support, engineering, marketing, and legal operations. Uncontrolled adoption creates hidden compliance, financial, and reputational liabilities.
1. Privacy & Confidentiality
Feeding proprietary customer data, non-public financials, or PII into public AI models without Zero Data Retention (ZDR) terms risks breaching GDPR, CCPA, and contractual client NDAs.
2. Hallucination & Accuracy
Large Language Models generate authoritative-sounding falsehoods. In customer-facing chatbots, pricing engines, or tax advice, unverified outputs create immediate financial liability.
3. Human-in-the-Loop Safeguards
Determining exactly when an employee must inspect, verify, and approve AI recommendations before output execution protects organizational accountability.
The Five Core Evaluation Dimensions
Our proprietary classification model evaluates individual business tasks across five quantitative pillars, yielding a clear Risk Index (0 to 100) and actionable mitigation safeguards: