Reg Compliance - AI Compliance Audit Model
Compliance Audit
by Neurometric⚖️ Legal & Compliance
Reg-Compliance is a task-specific model that compares company internal docs against specific regulations (e.g., GDPR, CCPA).
Reg Compliance is designed for Legal & Compliance workflows where speed, consistency, and control matter more than generic creativity. Instead of relying on a broad model to guess intent each time, this task-specific SLM is optimized for compliance audit and predictable output quality. That makes it easier to adopt in production pipelines where teams need reliable formatting, lower latency, and reduced hallucination risk.
Most teams integrate CRM records, internal docs, and workflow tools to automate repetitive language-heavy tasks with predictable outputs. This makes deployment practical for sales ops, customer success, legal, and operations teams that need answers grounded in their own data. Because the model is small and focused, teams can run it with efficient infrastructure while still meeting quality targets for the use case.
Compared with general-purpose models, focused SLMs like this one typically deliver better precision for narrow tasks, lower cost per request, and easier governance. You can start with the free tier, test the model against your business data, and scale usage through Neurometric APIs or ClawPack workflows when performance meets your benchmark.
Model: Qwen/Qwen3-4B-Instruct-2507
This task-specific SLM uses Qwen/Qwen3-4B-Instruct-2507 with a specialized system prompt. The model weights are identical to the base Qwen model — the task specialization comes from the system prompt and has been validated through our testing pipeline. Need better accuracy? We can fine-tune the model on your data for your specific use case.
Test Results
Example Input
Documents: - Title: Cookie & Tracking Notice; Doc Id: POL-COOK-003; Excerpt: We use cookies for functionality and targeted advertising. By continuing to use the site, you agree to cookies. Users can opt out of targeted ads by toggling settings in their account. We honor browser 'Do Not Track' signals when feasible. - Title: Vendor Data Processing Addendum; Doc Id: DPA-004; Excerpt: Processors must implement appropriate security measures and notify us of breaches within 72 hours. Subprocessors may be engaged with prior written consent. We do not define standard contractual clauses (SCCs) for international transfers. Regulations: - GDPR - CCPA Comparison Scope: Topics: - cookie consent - opt-out mechanisms - breach notification - subprocessors - international data transfers Jurisdictions: - EU - California
Expected Output
Gaps identified: Cookie notice relies on implied consent ('continuing to use') which is generally insufficient for GDPR for non-essential cookies; should implement granular opt-in prior to setting ad cookies. CCPA/CPRA requires a clear 'Do Not Sell or Share My Personal Information' link if ad tracking constitutes sharing; account-only opt-out may be inadequate. DPA aligns with GDPR breach notice expectations, but lacks explicit SCCs/transfer mechanism details for EU-to-non-EEA transfers. 'Do Not Track' handling is vague; consider honoring GPC for California where applicable.
Actual Model Response
Here is a structured comparison of the provided company documents against the relevant regulations GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act), within the specified comparison scope:
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🔍 Regulatory Comparison: GDPR & CCPA
| Topic | GDPR (EU) | CCPA (California) | Document Match | Compliance Status |
|-----------------------------|-------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------|------------------------|
| Cookie Consent | Requires clear, specific, and unambiguous consent for non-essential cookies. Must be given before data collection begins. Users must be informed of the purposes of cookies. | Requires businesses to disclose use of cookies and provide opt-out options for targeted advertising. Opt-out must be easy and accessible. | ✅ POL-COOK-003 states: "By continuing to use the site, you agree to cookies" — lacks explicit opt-in consent. <br> Users can opt out of targeted ads — partial compliance. | ⚠️ Partial (GDPR requires explicit consent; CCPA allows opt-out but not opt-in) |
| Opt-Out Mechanisms | Users must have a clear, accessible, and effective way to withdraw consent at any time. | Consumers have the right to opt out of the sale of personal data for targeted advertising. | ✅ POL-COOK-003 allows users to "toggle settings in their account" to opt out of targeted ads — meets CCPA opt-out requirement. | ✅ Compliant (with both regulations) |
| Breach Notification | Must notify data subjects and supervisory authorities within 72 hours of a breach (if likely to result in a risk to rights and freedoms). | Requires notification to consumers within 45 days of a breach (if likely to cause harm). | ✅ DPA-004 states: "Processors must notify us of breaches within 72 hours" — meets GDPR timeline. <br> No mention of consumer notification under CCPA. | ✅ GDPR compliant; ⚠️ CCPA gap (no consumer notification mechanism described) |
| Subprocessors | Subprocessors must be contractually bound to comply with GDPR. Requires prior written agreement and appropriate safeguards. | Subprocessors must be bound by similar privacy protections; businesses must disclose them to consumers. | ✅ DPA-004 states: "Subprocessors may be engaged with prior written consent" — meets GDPR requirement. <br> No explicit consumer disclosure under CCPA. | ✅ GDPR compliant; ⚠️ CCPA gap (lack of consumer disclosure) |
| International Data Transfers | Requires appropriate safeguards (e.g., SCCs, binding corporate rules) for transfers outside the EU. SCCs are standard and required unless alternatives exist. | No specific requirement for international transfers; however, data subjects have rights to know and opt out of sharing. | ❌ DPA-004 explicitly states: "We do not define standard contractual clauses (SCCs) for international transfers" — violates GDPR. <br> No mention of SCCs or safeguards. | ❌ Non-compliant with GDPR; ⚠️ CCPA not directly applicable |
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📌 Summary of Compliance Findings
| Jurisdiction | Compliance Status | Key Issues |
|------------------|------------------------|----------------|
| EU (GDPR) | ❌ Non-compliant | - No definition or use of SCCs for international data transfers (critical breach).<br> - "By continuing to use the site" implies implied consent, not explicit consent (violates GDPR). |
| California (CCPA) | ✅ Partially compliant | - Opt-out mechanism for targeted ads is present.<br> - Breach notification to consumers is missing.<br> - Subprocessor disclosures not made to consumers. |
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✅ Recommendations
GDPR Compliance Fixes:
Implement Standard Contractual Clauses (SCCs) or other adequate safeguards for international data transfers.
Replace "by continuing to use" with explicit, affirmative opt-in consent for cookies and tracking.
Clearly state the purposes of cookies and allow users to withdraw consent at any time.
CCPA Compliance Enhancements:
Add a clear consumer right to opt out of data sales (especially targeted advertising).
Include a breach notification process that informs affected consumers within 45 days.
Disclose **sub
Capabilities
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Frequently asked questions
Does Reg Compliance work with CRM systems?
Yes. Reg Compliance is built to work with CRM systems, internal docs, and CSV/JSON pipelines. Most teams connect existing APIs or scheduled exports and map records into prompt-ready JSON.
What data format does this model accept?
You can send plain text or structured JSON. For compliance audit, teams usually pass normalized records with field names, context notes, and output constraints.
Why use a task-specific SLM for compliance audit?
Task-specific SLMs are tuned for one business outcome, so they are often more consistent and cost-efficient than general models for repetitive production workflows.
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Need better performance?
We can fine-tune this model on your data for higher accuracy on your specific use case.