AccuNexum

Say yes to AI
without legal saying no.

AI governance is decision governance, not asset governance. We help Fortune 500 enterprises in healthcare, financial services, insurance, and the public sector govern the consequential decisions where AI is already involved — built to survive deposition, regulatory subpoena, and the board's next question.

Request a BriefingSee the Engagements

The Problem

AI Governance Is Not Optional

Healthcare organizations are deploying AI faster than their governance can keep up. Models touch clinical decisions, coverage determinations, patient communications, and revenue cycles — often without a documented assessment of who reviews them, what risks they carry, or what happens when they fail.

A new category of legal exposure is emerging that traditional HIPAA compliance does not address. Class actions over algorithmic claim denials and AI-driven coverage decisions are testing the legal theory that algorithmic decisions without genuine human oversight constitute breach of duty. If the theory holds, the precedent reshapes AI governance economics across both payer and provider sectors.

When the regulator calls — about an AI decision, a data breach, a vendor cascade, or anything else — “we trusted the vendor” is not a defense. Section 1557, HTI-1, the FDA, state AI bills, and the NAIC Model Bulletin all assume the organization can demonstrate a defensible governance program. Most cannot.

AccuNexum closes that gap with a framework rigorous enough for regulatory scrutiny and a platform operational enough for the people doing the work.

The Stakes

The Next Major Healthcare Exposure Event Will Not Be a Database Breach.

It will be an AI lawsuit. The cases below are the leading edge of a category of legal exposure traditional HIPAA compliance does not address. AccuNexum was built specifically for this category, with secondary value in regulatory response defensibility for the broader healthcare environment.

AI Liability — Coverage Decisions

Cigna PXDX Algorithm

A 2023 class action alleges Cigna used an algorithm to deny claims at scale without genuine physician review — with average physician review time reported at 1.2 seconds.

What AccuNexum directly prevents

Domain 2 forces documented human oversight before deployment. Domain 3 Template 4 requires Coverage Decision impact assessment. Domain 5 mandates decision-rights clarity. Domain 4 surfaces denial pattern anomalies before they become class actions.

AI Liability — Clinical Decisions

UnitedHealth / NaviHealth

A 2023 class action alleges nH Predict was used to deny Medicare Advantage post-acute care with a reported 90% error rate when challenged. Senate Subcommittee report followed in 2024.

What AccuNexum directly prevents

Domain 3 requires pre-deployment Algorithmic Impact Assessment across five lenses including bias and equity. Domain 4 Monitoring Intelligence detects accuracy and equity drift. Domain 5 Escalation Protocol routes systemic disparities to the AI Governance Committee. The 90% error rate would not survive a working monitoring program.

Vendor Cascade

Change Healthcare Ransomware

The February 2024 attack on Change Healthcare disrupted U.S. claims processing for weeks. UnitedHealth disclosed $872M+ in initial costs. Estimated 100M+ individuals affected.

Where AccuNexum reduces exposure

AccuNexum cannot prevent another organization’s cyberattack. Domain 6 (Vendor Management) forces categorization of critical foundation-tier vendors, continuous monitoring of vendor risk posture, contractual provisions for incident notification and audit rights, and documented continuity planning — changing how an organization is exposed to vendor cascade events.

Honest scope. AccuNexum is not a cybersecurity tool, a SIEM, or a privacy program. It does not prevent ransomware, insider theft, or configuration errors. What it does: govern AI deployments before they create liability, and provide the documented governance record that shapes regulatory inquiry outcomes when something does go wrong — for any reason.

The Framework

The AccuNexum Framework

Seven domains. One coherent system. The operating substrate underneath every engagement — designed for defensibility, organized around the consequential decision, not the AI asset.

1

Decision Register & Classification

A tiered catalog of the consequential decisions where AI is involved — clinical, financial, regulatory, employment, custodial — with named owners and exposure tiers. Inventories of AI tools are no longer actionable; the unit of analysis is the decision.

2

Intake & Approval

A single defined process every AI-influenced decision class passes through before production. Four review tracks calibrated to exposure tier and severity.

3

Risk, Bias & Equity Assessment

Algorithmic Impact Assessment across five lenses — algorithmic, bias and equity, safety, privacy, cybersecurity — with failure-mode mapping against the canonical AI governance failure modes.

4

Autonomy Envelopes & Lifecycle Controls

What the system is permitted to decide, under what conditions, with what fallbacks. Pre-deployment validation, hyper-monitoring, drift detection, change management, and kill-switch criteria with named approvers.

5

Decision Authority & Governance Bodies

Named accountability at every escalation tier, with explicit transfer protocols. The AI Governance Committee, board oversight, escalation paths — decisions made by the right people, in the right venue, on the record.

6

Vendor & Third-Party Management

Five-category vendor taxonomy. Due-diligence rigor calibrated to category. Contract clause libraries for BAAs, foundation models, and sensitive decision classes.

7

Audit, Documentation & Regulatory Response

Per-decision evidentiary trail designed to survive deposition, regulatory subpoena, and class-certification motions. Audit workpapers, regulatory inquiry response, litigation hold, annual governance reporting.

The Platform

The AccuNexum Operating Platform

The framework is the substance. The platform is how the work actually gets done.

AccuNexum's operating platform is AI-native, multi-tenant, and built for healthcare governance teams. It implements the full seven-domain framework, with AI capabilities embedded in the workflow — not as features bolted on, but as the way the platform operates.

What it does

  • ·Classifies new AI use cases against framework definitions, with explicit reasoning
  • ·Drafts Algorithmic Impact Assessments that humans then review and finalize
  • ·Surfaces similar past decisions to support risk acceptance and conditional approval
  • ·Monitors deployed AI for drift, bias, and predictive risk
  • ·Accelerates incident and regulatory response with cross-client pattern intelligence
  • ·Prepares AIGC meeting materials, drafts minutes, tracks action items
  • ·Personalizes the framework to the client’s vertical, size, and regulatory exposure

What it requires of you

The judgment. The decisions. The accountability. The platform doesn't replace governance — it makes governance possible at the scale and speed healthcare AI now demands.

Self-governed by the same framework.

Every AI capability the platform operates is itself a registered Use Case under the framework, with its own risk classification, AIA, monitoring, and audit trail. We practice what we sell.

For Whom

Fortune 500 enterprises. Named executive sponsors.

Built for organizations where AI has been entering through multiple channels — built, bought, embedded, and shadow — for eighteen months or more, and where executive accountability for AI decisions cannot be delegated.

Healthcare

Health systems, payers, and life-sciences organizations deploying AI in clinical decision support, prior authorization, claims, SaMD, and post-market surveillance — under HIPAA, HHS Section 1557, FDA, NAIC, and state law.

Financial Services & Insurance

Banks, asset managers, and insurers deploying AI in credit decisioning, fraud triage, underwriting, and claims adjudication — under CFPB, FRB, OCC, NAIC, and state algorithmic accountability law.

Public Sector

Federal and state agencies deploying AI in benefits adjudication, custodial decisions, regulatory triage, and employment — under EU AI Act adequacy, OMB M-24-10, and state-level public-sector AI mandates.

Typical sponsors

General Counsel · Chief Risk Officer · Chief Compliance Officer · Chief Medical Officer · Audit Committee · Board of Directors

How We Engage

Three Engagements. One Thesis.

Designed as a coherent product line and a natural sales sequence — diagnostic, through high-stakes deployment, to standing executive accountability. Most enterprises enter at the Decision Risk Map and move into Autonomy Envelope Design for the highest-exposure use cases it surfaces.

01

Decision Risk Map

The diagnostic.

4–6 weeks · fixed fee

Typical sponsors · General Counsel · Chief Risk Officer · Chief Compliance Officer · Chief Medical Officer

Identify the consequential decisions in your enterprise where AI is already involved, classify them by exposure tier, and deliver a sequenced remediation backlog the board can sign off on.

  • ·Decision register — tiered catalog of consequential decisions, named owners, decision authority documented
  • ·Exposure classification — clinical, financial, regulatory, employment, custodial; severity tiers
  • ·Decision-authority gap analysis — where named accountability and de facto authority diverge
  • ·Failure-mode mapping — each decision class evaluated against the six canonical AI governance failure modes
  • ·Sequenced remediation backlog with effort and risk estimates
  • ·Board-ready executive readout
02

Autonomy Envelope Design

The flagship.

8–12 weeks · fixed fee or milestone

Typical sponsors · General Counsel · Chief Risk Officer · Chief Medical Officer · Operational owner

Design and operationalize the governance regime for one high-stakes AI decision system. The deliverable is the autonomy envelope — what the system is permitted to decide, under what conditions, with what fallbacks — documented to survive deposition.

  • ·Autonomy envelope specification — scope of authority, conditions, fallbacks
  • ·Decision authority register — named accountability at every escalation tier, transfer protocols
  • ·Validation regime — prospective evaluation, performance floor, demographic-performance testing, drift monitoring
  • ·Telemetry and audit specification — per-decision evidentiary trail
  • ·Kill-switch criteria with named approvers and pre-authorized procedures
  • ·Human-in-the-loop design — accountable review, not theater
  • ·Implementation roadmap with engineering and process work clearly separated
03

Fractional Chief AI Decision Officer

The seat at the table.

6–12 months · executive day-rate retainer

Typical sponsors · CEO · Board · Audit Committee · General Counsel

A standing executive accountable for the enterprise AI decision regime — alongside the General Counsel, Chief Risk Officer, and Chief Medical or Compliance Officer. This role does not yet exist on most org charts. It will be standard by 2028.

  • ·Named executive accountability with explicit authority and defined scope
  • ·Quarterly decision-portfolio review with the audit committee or board
  • ·Continuous decision-class governance — new use cases enter the framework before deployment
  • ·Cross-functional alignment across legal, compliance, clinical/operational, and engineering
  • ·Regulatory readiness — EU AI Act, FDA SaMD, HHS Section 1557, state algorithmic accountability
  • ·Crisis response — qualified expertise already named, briefed, and at the executive table

This is not staff augmentation. Not a tool sale. Not a model-validation report. The work is closer to fiduciary advisory than to consulting — standing accountability for the consequential decisions your organization cannot afford to delegate.

About

About AccuNexum

AccuNexum was founded to address a structural gap in healthcare AI deployment: the absence of a defensible governance framework rigorous enough for the regulatory environment and operational enough for the teams doing the work.

The AccuNexum Framework synthesizes HIPAA Privacy and Security Rules, HHS HTI-1 / DSI, Section 1557, FDA SaMD and AI/ML guidance, NIST AI Risk Management Framework, ISO 42001, NAIC Model Bulletin, and material state AI law into a single coherent operating model across seven domains.

The AccuNexum Operating Platform implements that framework in production — multi-tenant, AI-native, designed for healthcare governance teams and the consulting practices that support them.

Based in the United States. Working with health systems, health plans, and life sciences companies nationwide.

Contact

Start where the exposure is.

AccuNexum is engaging selectively with Fortune 500 enterprises in healthcare, financial services, insurance, and the public sector where AI now influences consequential decisions and executive accountability cannot be delegated.

Most engagements begin with a Decision Risk Map — a four-to-six-week diagnostic that the General Counsel, Chief Risk Officer, and audit committee can sign off on. If you are responsible for AI risk in your organization, or asking “who is accountable for our AI decisions?” and finding no defensible answer on the current org chart, we'd like to hear from you.

sales@accunexum.com