AI, Privacy, and Data Security Counsel for Growth-Focused Companies

The “right time” is defined by your next pivotal transition—whether that is an M&A exit, a series-round diligence, or a cyber-insurance renewal. Waiting for a breach or a demand letter means your governance is already fixed in stone. Early involvement allows us to architect a defensible posture that reduces remediation costs and prevents “deal-kill” findings during technical diligence.

We don’t just deliver a compliance checklist; we build the risk architecture for your data. This includes negotiating high-stakes Data Processing Agreements (DPAs), managing cross-border transfer impact assessments (TIAs), and ensuring your internal AI acceptable-use policies don’t inadvertently waive trade secret protections under the VUTSA or DTSA.

Beyond simple exfiltration, the upcoming litigation risk is tied to “Agentic AI Liability”—where autonomous tools make unauthorized commitments or mishandle regulated datasets. Exposure often overlaps with statutory claims under the VCDPA, consumer protection theories, and “failure to supervise” claims regarding third-party SaaS vendors.

AI adoption almost always outpaces governance. “Shadow AI” occurs when employees feed proprietary code, customer lists, or sensitive financial data into public LLMs to increase productivity. Without a disciplined governance framework, this can result in the permanent loss of trade secret status and a breach of contractual confidentiality obligations to your own clients.

Possibly. Many standard MSAs include broad “Product Improvement” or “De-identified Data” clauses that allow vendors to ingest your proprietary data to train their competitive tools. For companies with high-value datasets, this is a material threat. We help clients negotiate data-use restrictions and “clean room” protocols that preserve data sovereignty and prevent your enterprise value from being harvested by your vendors.

In modern tech stacks, data is often scattered across unvetted vendors and legacy systems with no centralized ownership. During a liquidity event, this fragmentation is a red flag. We help companies centralize their Data Lifecycle Mapping, ensuring that when you are forced to prove your security controls match your representations, the evidence is forensic and indisputable.

For companies operating across multiple states, privacy compliance rarely turns on a single law. It usually turns on whether the business can function across a growing patchwork of state requirements, especially in larger markets like California, Texas, Colorado, Connecticut, and Virginia.

That matters because the differences are not just technical. One state may emphasize consumer rights requests, another opt-out mechanics, another risk assessments or cybersecurity audits, and another automated decision-making or profiling rules. California remains especially consequential because of the CCPA/CPRA regime and related regulations, while other states such as Colorado, Connecticut, Texas, and Virginia add their own operational requirements.

For most companies, the practical question is not whether to build fifty separate programs. It is how to build a privacy framework that can scale across jurisdictions without creating operational drag. We help clients structure that framework so the business can operate nationally while staying aligned with the states that matter most to its customers, data flows, and risk profile.