Enterprise AI Legal-Tech & Governance EU AI Act Fines Up to €35M or 7% Global Turnover

Protect Your Business from AI Liability, IP Leakage & Regulatory Non-Compliance

We help engineering companies, tech startups, and enterprises establish auditable AI Acceptable Use Policies (AUP), prevent proprietary code and trade secret leaks into public LLMs, perform dataset copyright provenance audits, and ensure airtight compliance with the EU AI Act and NIST AI RMF 1.0.

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The 4 Major AI Liabilities

1. Shadow AI & Code Exfiltration Engineers pasting proprietary algorithms, API keys, or trade secrets into public consumer AI tools without data retention opt-outs.

2. Dataset Copyright & GPL Poisoning Fine-tuning commercial models on unvetted scrapings, potentially importing GPL/copyleft viral licenses or copyrighted material.

3. EU AI Act High-Risk Penalties Deploying AI in human safety, critical infrastructure, credit scoring, or biometric categorization without mandatory Annex IV documentation.

4. Unvetted Vendor LLM Agreements Relying on external model APIs whose Terms of Service permit training on user prompts or lack enterprise HIPAA/GDPR SLAs.

Enterprise Consulting Pillars

Comprehensive AI Governance & Legal-Tech Protection

Turn vague AI guidelines into enforceable technical controls, contracts, and regulatory dossiers.

Corporate AI Acceptable Use Policy (AUP)

A legally robust, engineer-friendly policy dictating precisely which tools (ChatGPT, Claude, GitHub Copilot, Cursor) are permitted, which data tiers may be entered, and how code authorship is validated.

IP ownership & copyright indemnity clauses
Employee onboarding & training guidelines
Zero-retention configuration checklist

Shadow AI & DLP Architecture

Implement automated enterprise Data Loss Prevention (DLP) proxies to block secret keys, source code snippets, and customer PII before queries ever reach cloud model APIs.

Microsoft Presidio PII anonymizer filters
Network egress audits for rogue AI tools
Secure private gateway proxy setup

Training Data Provenance & Clean-Room Audits

Ensure your fine-tuned models and RAG knowledge bases are free from toxic datasets, GPL viral code contagion, and non-commercial scraped web assets that could trigger litigation.

Open-source license reconciliation (MIT vs GPL)
Synthetic data validation & bias checks
Clean-room documentation audit certificate

EU AI Act Readiness & Classification

Classify your software under the European Union AI Act (Minimal, Transparency, High-Risk, Prohibited) and assemble the mandatory Annex IV technical documentation package.

Risk Management System (RMS) according to Art. 9
Human oversight mechanisms & model logging
Post-market monitoring plan drafting

NIST AI RMF 1.0 Implementation

Operationalize the National Institute of Standards and Technology AI Risk Management Framework across your organization's Gov, Map, Measure, and Manage functions.

AI Risk inventory & asset categorization
Metrics for trustworthiness & fairness
Continuous executive governance dashboards

Third-Party Model Vendor Due Diligence

Vetting external AI SaaS providers, foundational model vendors (OpenAI, Anthropic, AWS Bedrock), and sub-processors for strict regulatory and intellectual property alignment.

Zero-day retention agreement verification
SLA & uptime compliance review
Vendor risk assessment scorecard

Interactive Assessment

Evaluate Your Enterprise AI Liability Exposure

Select your operational profile to get an immediate benchmark of your regulatory exposure and recommended governance actions.

Primary AI Deployment Type

Data Sensitivity Level

Customer Geographic Market

Estimated Liability Level

MODERATE RISK

Confidential business data is at risk of exposure without an enterprise zero-retention SLA and formal AUP.

Priority Action: Deploy an Employee AI Acceptable Use Policy and configure gateway DLP filters.

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Transparent Consulting Tiers

AI Governance & Audit Packages

Turnkey deliverables engineered to satisfy corporate compliance, cyber insurance underwriters, and regulatory bodies.

Startup AUP & Policy Pack

Ideal for startups and growing software firms introducing generative AI tools to staff.

$1,200 / one-time

Custom Employee AI Acceptable Use Policy
Approved Tool Roster & Data Tier Matrix
Zero-Data-Retention vendor configuration guide
IP ownership & copyright indemnity terms
EU AI Act Annex IV technical dossier

Select Startup Pack

Full Enterprise Governance

Comprehensive framework alignment for enterprises deploying internal RAG or custom models.

$2,800 / one-time

Everything in Startup Pack, plus:
NIST AI RMF 1.0 Gap Analysis & Roadmap
Data Loss Prevention (DLP) architecture plan
Third-party vendor AI risk scorecard (up to 5 tools)
Executive Risk Presentation & Board Briefing

Select Enterprise Pack

EU AI Act & Clean-Room

For high-risk systems, medical devices, automotive AI, or commercial model creators.

$4,500 / one-time

Everything in Enterprise Pack, plus:
Turnkey EU AI Act Annex IV Technical File
Training Dataset Copyright & License Provenance Audit
Human Oversight & Post-Market Monitoring System
30 Days Direct On-Demand Legal-Tech Support

Select Regulatory Pack

Frequently Asked Questions

Enterprise AI Policy & Governance FAQs

Yes. Under trade secret statutes worldwide, trade secret protection can be legally forfeited if the owner fails to exercise "reasonable measures" to preserve confidentiality. Pasting proprietary source code or financial projections into default consumer AI accounts (which may utilize inputs for model retraining) destroys confidentiality. Our AUP and DLP controls establish the documented "reasonable measures" required to defend your IP in court.

Prohibited AI practices are banned as of early 2025. General-purpose AI (GPAI) model rules take effect mid-2025, and high-risk system regulations fully apply by 2026. Penalties for non-compliance reach up to €35,000,000 or 7% of total worldwide annual turnover for the preceding financial year. Even companies outside the EU are subject to the Act if their AI system's output is used within the EU single market.

We deploy automated signature scanning and lexical overlap tools across your pre-training and fine-tuning corpus to detect copyleft licenses (GPL, AGPL), non-commercial academic licenses (CC-BY-NC), and scraped proprietary assets. We provide a documented Clean-Room Provenance Log detailing dataset origin, scrubbing steps, and synthetic augmentation.

Yes, absolutely. Even if you do not train models internally, your employees use these tools daily. Without an approved AUP, employees frequently mix client PII, confidential contracts, or unreleased product designs into chat boxes. Furthermore, commercial cyber insurance policies increasingly demand proof of internal AI controls before underwriting claims related to data breaches.

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