“We are adding generative AI. What do our Terms and Privacy Policy need to say?”
We examine inputs, outputs, provider terms, data retention, training, user expectations, accuracy, human review, and the allocation of responsibility.
AI, data privacy & product counsel
Legal guidance for the data inside the product.
Build terms, privacy disclosures, data-use provisions, and vendor relationships around what your AI or technology product actually does—not around generic policies that create new risk.
Nationwide transactional technology matters. Lissette Eusebio is admitted in Florida, New York, and the District of Columbia.
AI productsTerms, disclosures, risk allocation
PrivacyPolicies tied to real data flows
Commercial dataDPAs and customer commitments
GovernancePractical operating guardrails
Where the legal question starts
Call before the product promise outruns the product.
AI and privacy work sits at the intersection of user experience, engineering, vendors, customer commitments, and public claims. These moments deserve more than a template.
“A customer sent a DPA, security exhibit, and AI questionnaire.”
We coordinate the legal answers with actual systems and vendors, redline obligations the company cannot support, and align the package with the core agreement.
“Our policy no longer matches the product or our vendors.”
We trace the relevant data flows, identify disclosure and contract gaps, and update the public and commercial documents around the real operation.
“The product may reach younger users or handle higher-risk information.”
We assess age, consent, minimization, disclosure, vendor, retention, and product-design issues, including COPPA and other applicable privacy considerations.
AI and privacy counsel
Connect the legal documents to the operating system.
The goal is a legal stack the business can defend, explain, and follow.
AI terms & disclosures
Inputs, outputs, model limitations, prohibited uses, human review, ownership, responsibility, and product claims.
Privacy Policies
Collection, use, sharing, cookies, analytics, choices, retention, rights, contact points, and jurisdictional notices.
Data Processing Agreements
Roles, instructions, subprocessors, security, incidents, rights requests, deletion, audit, and international transfers.
AI & cloud vendor terms
Data-use rights, training, confidentiality, security, service changes, model access, indemnity, and downstream risk.
GDPR, COPPA & U.S. privacy
Practical issue-spotting based on users, geography, data categories, business model, and product design.
Responsible AI governance
Review points, acceptable-use rules, documentation, vendor intake, escalation, and human decision-making controls.
Documents follow reality
Start with how the product works.
We ask the questions needed to understand the product, users, data, vendors, contracts, and launch plan. Then we build the legal layer around that reality.
Map the decision
Identify the launch, customer, vendor, or compliance decision driving the work.
Trace the data
Understand what enters the system, where it goes, who can use it, and how long it remains.
Reconcile the promises
Align user-facing claims, customer contracts, vendor terms, and operational controls.
Build practical guardrails
Create documents and review points the team can actually operate.
AI and privacy questions
Before the next release.
Legal language should explain the product clearly without promising what the system cannot guarantee.
Does an AI product need special Terms of Service and privacy language?
Often, yes. The documents may need to address prompts and inputs, model or API providers, ownership and permitted use of outputs, training, accuracy, human review, prohibited uses, data retention, security, disclosures, and responsibility for third-party tools.
Can one Privacy Policy cover a website, SaaS platform, and AI feature?
It can only do so accurately if it describes the actual data flows, uses, disclosures, choices, retention, and jurisdiction-specific rights across those services. A policy should follow the product and vendor architecture rather than rely on generic language.
Do you advise technology companies outside Florida on AI and privacy matters?
Eusebio Law handles transactional technology matters for clients across the United States. Lissette Eusebio is admitted in Florida, New York, and the District of Columbia. Local or specialized counsel may be coordinated when a matter requires advice outside that scope.
What is the difference between a Privacy Policy and a DPA?
A Privacy Policy explains the company's data practices to individuals. A DPA allocates privacy and security obligations between businesses when one processes personal data for another. Many technology companies need both, but each serves a different audience and legal function.
Build the legal layer
Bring us the AI feature, data flow, or privacy question in front of you.
We will identify the appropriate scope and explain the next step.