SERVICES
We begin with the problem, not the methodology.
Every engagement begins with a specific problem and moves toward a working solution. We help organizations make the difficult decisions they have been deferring or structuring poorly, decisions about responsibility, liability, and the infrastructure required to deploy AI where the stakes are human. Our work spans the full arc from strategic advisory to technical implementation, because oversight that exists only in documents fails in the face of reality.
Healthcare AI Governance
Health systems deploying clinical AI face a question that no vendor contract or compliance checklist adequately answers. When an AI-assisted recommendation contributes to a bad outcome, where does responsibility migrate? The physician who followed the recommendation, the institution that deployed it, the vendor who built it, and the insurer who covered the encounter each occupy positions in a liability architecture that most organizations have never explicitly designed.
We help health systems, clinical AI vendors, and payers map the chain from algorithm output to clinical action, identifying where human override is preserved or eroded, where documentation practices create or foreclose legal exposure, and where the oversight structure would fail under regulatory scrutiny. The engagement extends from advisory through implementation, including the design of monitoring systems, audit trails, and escalation protocols that make accountability real within clinical workflows and EHR integrations.
Enterprise AI Risk and Implementation
Most organizations have an AI policy. Very few have the infrastructure to make a difficult decision at operational speed when that policy is tested. The distance between a stated principle and a real-world situation, a model flags a transaction at 2 AM and the override protocol is ambiguous, is where institutional risk compounds. Aspiration without infrastructure is decoration, and infrastructure requires technical systems.
We work with enterprises in regulated industries to stress-test their AI governance against realistic failure scenarios, identify the decisions their current structures cannot actually make, and build the connective tissue between policy language and production reality. This includes accountability mapping, escalation design, model risk documentation, and the implementation of monitoring, alerting, and human-in-the-loop systems that function under pressure.
Vendor Liability Advisory
AI companies building products for regulated industries carry liability exposure that most product and engineering teams have not fully internalized. The way a model communicates confidence, the manner in which human override is designed, the specificity of intended-use documentation, and the contractual allocation of responsibility between vendor and customer all function as de facto liability positions, whether or not anyone has framed them in those terms. Design decisions carry oversight implications that most product teams only recognize in retrospect, usually when the liability has already materialized.
We advise AI vendors on how their product architecture and commercial structures create exposure, and we help them build the technical and procedural safeguards that make their position defensible. This includes confidence calibration strategy, override and audit system design, post-market surveillance planning, and contractual frameworks that allocate responsibility in ways that are both commercially viable and legally sound.
Board and Investor AI Advisory
Boards, audit committees, and senior leadership teams increasingly face fiduciary questions about AI that existing oversight structures were not designed to address. The AI ethics statement may exist, but the deeper question is whether anyone in the accountability chain understands where the institution has delegated consequential judgment to automated systems, what exposure that delegation creates, and whether the technical and organizational infrastructure exists to intervene when something goes wrong.
For private equity firms evaluating portfolio companies with AI exposure, we conduct diligence on oversight maturity, liability architecture, and the gap between an AI strategy deck and operational readiness. For boards and C-suite leaders, we design reporting structures and risk communication frameworks that enable genuine accountability.
Expert Engagement
As AI-assisted decisions enter medical records, claims adjudication files, and legal discovery, the need for expert perspective that spans clinical practice, legal doctrine, and AI product architecture is growing. We are available for expert witness engagements, litigation support, and regulatory consultation where the intersection of these domains is material to the matter at hand.
Engagement Structure
We work through advisory retainers, scoped project engagements, and intensive implementation sprints. Every engagement begins with a diagnostic conversation to determine whether our specific expertise matches the problem. We will tell you if it does not.
To discuss an engagement, reach us at nseshadri@tercetadvisory.com.