Our Process for Working With Law Firms

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 InterCore Technologies operates under a law-firm-appropriate security model designed for Am Law 200 / enterprise-grade security expectations–scale risk standards. Our process prioritizes data protection, contractual defensibility, and conservative AI implementation over experimental marketing tactics. 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.

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. ⚠️ Limitations: AI platform algorithms and ranking factors evolve continuously.

While our approach is based on documented research and practitioner observations, no vendor can guarantee specific visibility outcomes across generative AI systems. Measurement frameworks must account for this inherent uncertainty.

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.

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. ⚠️ Limitations: AI tool capabilities and security profiles evolve rapidly. Tools evaluated as low-risk today may introduce new risk factors through updates or changes in vendor ownership.

Our evaluation process is ongoing, but we cannot guarantee that tools remain risk-free indefinitely. Clients should conduct their own periodic vendor reviews as part of standard risk management processes.

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.

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.

For clarity and to set appropriate expectations, we explicitly do not: Work with confidential or privileged data in public AI systems — This restriction is absolute and applies to all AI platforms including ChatGPT, Google Gemini, Claude AI, Perplexity AI, Microsoft Copilot, and Grok Train AI models on client data — Client information never enters model training pipelines Operate without written agreements in place — NDAs and DPAs are executed before data access begins Use opaque or non-defensible tactics — All strategies must be explainable to general counsel and IT security teams Introduce tools or processes that create unnecessary discovery or reputational risk — Tool selection prioritizes defensibility over performance optimization 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.

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: 🔒 Security-First Architecture We assume a law-firm threat model from day one. Your IT security team and general counsel can review our documented controls, data handling procedures, and contractual framework.

We do not ask you to compromise on security to achieve marketing objectives. 📋 Vendor Review Readiness Our documentation, security questionnaire responses, and contractual templates are designed to pass law firm vendor review processes. We provide accurate representations, maintain audit trails, and respond to due diligence requests with specificity rather than generic marketing language. 🎯 Practice Area Expertise Since 2002, we have served law firms across every major practice area including personal injury , family law , criminal defense , estate planning , employment law , and immigration law . We understand practice-specific constraints, client sensitivity considerations, and competitive dynamics. 🌎 Nationwide Coverage With 35 physical offices across 24+ states including Los Angeles , New York , Chicago , Houston , Miami , and major markets nationwide , we provide local market expertise combined with national strategic oversight. ⚖️ Long-Term Relationship Focus We prioritize long-term client relationships over short-term revenue.

This means scoping engagements conservatively, communicating limitations honestly, and declining work that would create risk exposure for your firm. Our average client relationship spans multiple years.

How do you handle privileged or confidential information during engagements? We do not request, access, or process attorney-client privileged communications, work product, or confidential case information. Our work focuses on publicly available information, firm-approved marketing materials, and technical infrastructure that does not involve confidential data.

If an engagement requires access to analytics platforms or content management systems that might contain confidential information, we implement role-based access controls, conduct specific data classification exercises, and document which data elements are off-limits. When uncertainty exists about whether information is confidential, we default to treating it as restricted. What happens if a security incident occurs during our engagement?

We maintain documented incident response procedures with defined notification timelines. If a security incident occurs that may affect client data, we notify designated firm stakeholders according to contractually agreed timelines, typically within 24-72 hours of discovery depending on incident severity. Our incident response process includes containment procedures, forensic analysis where appropriate, remediation steps, and post-incident reporting.

We coordinate with your IT security and legal teams throughout the response process. How do you evaluate third-party AI tools before using them in our engagement? Our tool evaluation process examines multiple risk factors including security architecture, data retention policies, model training restrictions, contractual terms, and vendor stability.

We review terms of service for problematic clauses, verify encryption standards, and confirm that data will not be used for model training. Tools that store data indefinitely, claim broad rights to user inputs, or lack transparent security documentation are excluded regardless of their performance capabilities. We maintain an approved tool list and require written client approval before introducing new tools to active engagements.

Can you guarantee specific visibility outcomes across AI platforms like ChatGPT or Perplexity? No vendor can ethically guarantee specific AI platform visibility outcomes. AI systems use proprietary algorithms that evolve continuously, and ranking factors are not publicly documented.

Our approach focuses on strengthening the authoritative signals these systems already recognize, but we cannot control how individual platforms weight those signals. We provide measurement frameworks to track mention rates, citation patterns, and competitive positioning over time, but these metrics are observational. Claims of guaranteed rankings or citations across AI platforms should be viewed skeptically as they typically indicate either misunderstanding of how these systems work or willingness to use high-risk tactics.

How do your data protection practices compare to GDPR or CCPA requirements? Our data protection principles align with core requirements of both GDPR and CCPA, including data minimization, purpose limitation, access controls, and deletion rights. However, we do not represent legal compliance with these regulations as that determination depends on specific engagement facts and your firm’s own compliance obligations.

Our Data Processing Agreements can be structured to address GDPR processor obligations or CCPA service provider requirements. We recommend involving your firm’s privacy counsel in reviewing these agreements to ensure alignment with your compliance program. What is your process for handling subprocessors or third-party vendors?

We maintain a documented list of subprocessors who may access client data during service delivery. This typically includes infrastructure providers (cloud hosting, email services) and specialized technical vendors (analytics platforms, schema validation tools). Subprocessors are selected based on security posture and contractual protections.

Our Data Processing Agreements include subprocessor notification provisions. When we intend to add a new subprocessor who will access client data, we provide advance notice and opportunity to object. Subprocessors are bound by data protection obligations equivalent to our own commitments.

How long does it typically take to complete your vendor review process? Vendor review timelines vary by firm size and internal processes, but typically range from 2-6 weeks. We provide completed security questionnaires, insurance certificates, executed NDAs, draft DPAs, and supporting documentation at the outset to streamline the process.

For firms with expedited review tracks or pre-approved vendor categories, timelines can be shorter. We recommend beginning the vendor review process in parallel with engagement scoping discussions to avoid delays once scope is agreed. 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 InterCore Technologies 📞 (213) 282-3001 ✉️ sales@intercore.net 📍 13428 Maxella Ave, Marina Del Rey, CA 90292

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 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/ 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 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 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. Scott Wiseman CEO & Founder, InterCore Technologies Published: February 4, 2025 | Last Updated: February 14, 2025 | Reading Time: 14 minutes Contact Us 213-282-3001 sales@intercore.net