Our Process for Working With Law Firms

Security-First AI Implementation Designed for Am Law 200 Risk Standards

🎯 Key Takeaways

• Law-firm threat model: We assume Am Law–scale security and confidentiality requirements, not consumer marketing standards
• No confidential data in public AI: Client privileged or confidential information never enters public AI systems or model training pipelines
• SOC 2-aligned controls: Documented security policies, role-based access controls, vendor risk evaluation, and incident response procedures
• Contractual protections first: NDAs and Data Processing Agreements executed before accessing any client data
• Conservative AI approach: We improve information quality and authority rather than attempting to manipulate AI systems directly

Large law firms operate under fundamentally different risk parameters than consumer brands or traditional marketing organizations. Your firm’s reputation, client confidentiality obligations, and discovery exposure create unique constraints that most legal marketing vendors are not equipped to address. InterCore Technologies has developed a security-first process specifically designed to meet these requirements.

Our approach to Generative Engine Optimization (GEO) and AI-powered SEO services begins with a fundamental assumption: we are working within a law-firm threat model, not a marketing-agency one. This assumption governs every aspect of how we handle data, evaluate tools, scope risk, and structure engagements. We prioritize precision, defensibility, and predictability over experimentation.

Since 2002, InterCore has served law firms across all practice areas including personal injury, family law, and criminal defense. Our process has been refined through hundreds of engagements with firms that demand both technical excellence and operational security.

Our Approach to AI and Legal Marketing

How We Treat AI Systems

We do not attempt to manipulate or influence AI systems directly. This distinction is critical because it defines the boundary between defensible practice and reputational risk. Our methodology focuses on improving the quality, authority, and consistency of the information that AI platforms like ChatGPT, Google Gemini, Claude AI, Perplexity AI, Microsoft Copilot, and Grok are already trained to trust.

According to research published in the Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’24, Barcelona, Spain, August 25-29, 2024), generative AI platforms prioritize authoritative sources, factual consistency, and entity clarity when determining which content to cite or reference. Rather than attempting to game these systems, we strengthen the foundational signals they already rely on.

We treat AI systems as downstream consumers of information, not targets to be gamed. This philosophical distinction matters in vendor review processes, general counsel discussions, and long-term risk management.

What This Means for Your Firm

Our process focuses on:

• Working with authoritative, verifiable sources that AI systems already recognize as trustworthy
• Correcting inaccuracies and inconsistencies in how your firm’s information appears across the web
• Strengthening factual clarity around your firm’s entities, expertise areas, and market positioning
• Avoiding tactics that create reputational, legal, or discovery risk

This approach aligns with how we implement AI-powered web design and development and AI content creation services. Every technical decision is evaluated through the lens of long-term defensibility rather than short-term performance metrics.

Security and Data Protection Principles

We operate under a strict set of data protection principles for all law firm engagements. These principles are non-negotiable and apply regardless of engagement scope, timeline, or service type. They govern how we approach AI marketing automation, content development, technical implementations, and all other services we provide.

Data Minimization and Purpose Limitation

Data Minimization: We collect and process only the information necessary to perform agreed services. If a particular data element is not directly required to deliver the contracted engagement, we do not request or retain it. This principle reduces your firm’s exposure surface and aligns with privacy best practices recognized across legal and regulated industries.

Purpose Limitation: Client data is used solely for the contracted engagement and no other purpose. Data provided for technical SEO audit purposes, for example, is not used for content marketing, competitive analysis, or any other activity outside the defined scope. Cross-purpose data usage requires explicit written authorization.

Client Isolation and Model Training Restrictions

Client Isolation: Client data is logically segregated by engagement and never shared across clients. We maintain strict access controls that prevent cross-client data exposure. This isolation extends to our internal systems, third-party tools, and any AI-enabled platforms used in service delivery.

No Model Training: Client confidential or proprietary information is never used to train public or third-party AI models. This restriction is absolute. According to Pew Research Center (survey of 5,123 U.S. adults, February 24–March 2, 2025; published June 25, 2025), 34% of U.S. adults have now used ChatGPT, and 58% of adults under 30 have used it. As AI adoption accelerates, the risk of inadvertent data leakage through model training pipelines increases. We prevent this risk through tool selection and contractual controls.

These protections apply across all service lines, including estate planning marketing, employment law marketing, and immigration law marketing engagements where client sensitivity is particularly high.

Compliance Alignment

We maintain documented security controls aligned with SOC 2 Trust Services Criteria, with particular emphasis on security and confidentiality principles. While we do not represent certifications we do not formally hold, our operational security posture includes:

• Formal written security policies governing access, retention, and incident response
• Role-based access controls and least-privilege principles for all systems
• Secure, enterprise-grade infrastructure commonly used by large law firms
• Vendor and tool risk evaluation before introduction to client engagements
• Incident response and notification procedures with defined escalation paths

These controls are documented and available for review during vendor assessment processes. We provide accurate, auditable representations and do not overstate our compliance posture.

Artificial Intelligence Usage Standards

We take a conservative, controlled approach to artificial intelligence. AI is treated as an assistive capability, not an autonomous system. This distinction matters in risk evaluation, quality control, and long-term accountability.

What Data We Never Use in AI Systems

We categorically do not input confidential, privileged, or client-restricted data into public or consumer AI systems. This restriction includes:

• Attorney-client privileged communications
• Work product materials
• Client matter information
• Confidential business information
• Personally identifiable information (PII) of clients or opposing parties
• Case strategy documents or internal firm communications

AI-enabled tools are used only with publicly available or client-approved, non-confidential information. If there is any ambiguity about whether information qualifies as confidential, we default to treating it as restricted.

AI Tool Evaluation Process

Any AI-enabled tool under consideration for use in client engagements undergoes formal risk evaluation. This evaluation examines:

• Security posture: Encryption standards, access controls, authentication mechanisms
• Data retention policies: How long data is stored, where it is stored, and deletion procedures
• Model training restrictions: Whether user inputs are used for model training
• Contractual terms: Terms of service, data processing agreements, liability provisions
• Vendor stability: Financial viability, reputation, breach history

Tools that do not meet our evaluation criteria are not introduced to client engagements, regardless of their potential performance benefits. This applies to all services from AI PPC management to AI-powered local optimization.

Human Oversight Requirements

All AI-generated outputs are reviewed by humans prior to delivery. This includes content drafts, schema markup generated by our Attorney Schema Generator, technical recommendations, and any other deliverable where AI played a role in production. We do not deliver unreviewed AI outputs to law firm clients.

Human reviewers verify factual accuracy, contextual appropriateness, and alignment with the client’s established positioning and tone. This review layer serves as a critical control point against AI hallucination, factual errors, and stylistic inconsistencies.

Contractual Protections and Data Handling

Standard Agreement Framework

We routinely execute Non-Disclosure Agreements (NDAs) and Data Processing Agreements (DPAs) with law firm clients. These agreements are executed prior to receiving or accessing any confidential or personal data. We do not begin work that involves access to client systems, analytics platforms, or proprietary information until contractual protections are in place.

Our standard DPA includes:

• Clear definition of data controller and processor roles
• Permitted processing purposes and restrictions on secondary use
• Data security obligations and technical safeguards
• Subprocessor notification and approval mechanisms
• Data subject rights and cooperation obligations
• Breach notification timelines and procedures
• Data return or deletion protocols upon engagement completion

Client data remains the exclusive property of the client at all times. We claim no ownership interest in client data, analytics, or any information provided during the engagement.

Data Storage and Retention Policies

Client data is stored only in secure systems necessary to perform the engagement. We utilize reputable, enterprise cloud environments commonly used by large law firms, selected based on their security and compliance profiles. Data is logically segregated by client to prevent cross-client exposure or commingling.

Data is retained only for the duration required to deliver contracted services. Upon completion of the engagement or upon client request, data is returned or securely deleted in accordance with written instructions. Deletion procedures follow industry standards for secure data destruction, including overwriting or cryptographic erasure where applicable.

These policies apply uniformly across practice areas, whether we are supporting business law marketing, intellectual property law marketing, or any other specialization.

How Engagements Begin

Initial Scoping Process

To minimize risk and ensure alignment, engagements typically begin with clearly defined parameters:

• Clearly scoped use cases: Specific deliverables, timelines, and success criteria
• Defined data boundaries: Explicit agreement on what data will be accessed, how it will be used, and how long it will be retained
• Limited initial access: Principle of least privilege applied to system access, with expansion only as needed
• Explicit in-scope and out-of-scope definitions: Written documentation of what activities are included and what activities are excluded

We prefer to expand scope only after comfort is established. Many of our long-term client relationships began with narrow, low-risk engagements that demonstrated our process and security discipline before expanding into broader initiatives like multi-location marketing campaigns or comprehensive ROI-driven strategies.

Risk Boundary Definition

Early in the engagement process, we work with your team to define explicit risk boundaries. This includes:

• What types of data are categorically off-limits (e.g., case files, client lists, financial records)
• What approval processes are required for tool or vendor introduction
• What notification procedures apply if risk factors change during the engagement
• What escalation paths exist if security incidents or concerns arise

These boundaries are documented and respected throughout the engagement. Changes require written approval from designated firm stakeholders.

What We Will Not Do

For clarity and to set appropriate expectations, we explicitly do not:

These restrictions are foundational to our process and do not change based on project urgency, budget, or competitive pressure. Firms seeking aggressive or experimental approaches that operate outside these boundaries should work with vendors whose risk tolerance aligns with those objectives.

Why Law Firms Choose Our Process

Our goal is straightforward: to be a vendor law firms trust because our process is predictable, conservative, and defensible — not because it is experimental or aggressive. Law firms across the United States choose our process for several key reasons:

Frequently Asked Questions

Ready to Discuss Your Firm’s Requirements?

If you are evaluating AI-related visibility, reputation, or information accuracy initiatives and require a law-firm-appropriate process, we welcome an initial conversation focused on scope, risk boundaries, and alignment.

Schedule a Consultation

References

1. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2024). GEO: Generative Engine Optimization. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’24), Barcelona, Spain, August 25-29, 2024, pp. 5-16. DOI: 10.1145/3637528.3671900
2. Sidoti, O. (2025, June 25). ChatGPT use among Americans roughly doubled since 2023. Pew Research Center. Survey of 5,123 U.S. adults conducted February 24–March 2, 2025. https://www.pewresearch.org/short-reads/2025/06/25/34-of-us-adults-have-used-chatgpt-about-double-the-share-in-2023/
3. American Institute of Certified Public Accountants (AICPA). (2017). SOC 2® – SOC for Service Organizations: Trust Services Criteria. https://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/sorhome.html
4. European Parliament and Council of the European Union. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation). Official Journal of the European Union, L 119/1. https://eur-lex.europa.eu/eli/reg/2016/679/oj
5. State of California. (2018). California Consumer Privacy Act of 2018 (CCPA), California Civil Code §§ 1798.100–1798.199. https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5

InterCore Technologies has spent 23 years refining a process that meets the unique requirements of law firms evaluating Generative Engine Optimization, AI-powered SEO, and comprehensive legal marketing strategies. Our process prioritizes what matters most to law firms: defensibility, security, and long-term reputational protection.

We recognize that law firms evaluating AI-related initiatives face a complex landscape of vendor claims, rapidly evolving technology, and uncertainty about appropriate risk thresholds. Our role is to provide a conservative, transparent process that your IT security, general counsel, and executive leadership can evaluate and approve with confidence.

Whether your firm is seeking to improve visibility across AI platforms, correct inaccurate information appearing in generative AI responses, or implement broader AI marketing automation strategies, our process provides the security foundation required for law-firm engagements. We welcome conversations focused on your specific requirements and risk tolerance.