AxonFlow for Healthcare

The Challenge

Healthcare AI is not a generic LLM problem

When an AI agent accesses a patient record, every interaction falls under regulatory scrutiny. Compliance officers need to answer specific questions: what data left the system, who approved the action, and where is the evidence.

What regulators require

HIPAA Privacy Rule — minimum necessary standard for PHI disclosure. AI agents must not send more patient data to an LLM than a task requires.
HIPAA Security Rule (164.312) — access controls, audit controls, and transmission security for electronic PHI.
HITECH Act — breach-notification duties can apply after an impermissible use or disclosure of unsecured PHI. Whether an incident is reportable depends on the facts, safeguards, and required risk assessment.
FDA AI/ML device guidance — AI-enabled medical-device teams may need lifecycle evidence, change-control planning, and performance monitoring depending on the product and regulatory pathway.
EU AI Act (Art 13–14) — transparency and human oversight for high-risk AI systems, including medical devices.

Why generic gateways fail

Incomplete sensitive-data coverage — healthcare teams must combine supported identifier detection with custom policies for organization-specific fields such as MRNs and clinical workflow context.
No human-in-the-loop — consequential clinical and administrative workflows often need qualified human review before execution. Logging after the fact cannot substitute for that control.
No decision-level audit — reviewers need identity, timestamp, policy verdict, and outcome context without unnecessarily duplicating PHI in the audit record.
No evidence export — compliance teams need to pull a specific time range and hand it to an auditor as a self-contained package.
No circuit breaker — when policy-violation or error thresholds are exceeded, teams need a way to block subsequent governed requests while they investigate.

Use Cases

Where AxonFlow fits in healthcare AI

Each use case maps to specific AxonFlow capabilities: healthcare-oriented PII detection, HITL approval gates, MCP connector governance, audit trails, and circuit breakers.

Prior Authorization Agents

AI agents that evaluate prior auth requests against payer criteria. HITL approval gates route configured high-cost procedures to a human reviewer before approval or denial. Governed decisions record the reviewer's identity and timestamp.

HITL Approval Audit Trail Policy Enforcement

Clinical Decision Support

AI-assisted diagnosis and treatment recommendations. AxonFlow detects sensitive identifiers (SSN, date of birth, credit card numbers with Luhn checksum validation) and redacts it before the data reaches the LLM. The resulting decision record can link the governed request to the requesting clinician.

PII Detection PII Redaction Decision Audit

Patient Communication Copilots

AI copilots that draft discharge instructions, appointment reminders, or patient portal responses. PII redaction strips identifiers before the prompt reaches the LLM. The governed response is logged with the policy verdict so compliance can inspect the recorded outcome.

PII Redaction Policy Enforcement Response Logging

Medical Coding Automation

AI agents that assign ICD-10 and CPT codes from clinical notes. AxonFlow governs the MCP connectors that access EHR systems, enforcing which fields the agent can read and logging governed connector requests and responses. Connector-level policies can constrain allowed operations and data paths.

MCP Governance Access Control Connector Policy

Adverse Event Monitoring

AI systems that scan clinical data for safety signals. AxonFlow can block subsequent governed requests when configured error or policy thresholds trip, or when a reviewer activates the circuit manually. Evidence exports support internal investigation and preparation of regulatory evidence.

Circuit Breaker Evidence Export Post-Market Surveillance

Regulatory Mapping

How AxonFlow capabilities map to healthcare regulations

AxonFlow is not a compliance certification. It provides runtime capabilities — detection, gating, logging, and export — that help engineering teams build systems that satisfy regulatory requirements. Your compliance team makes the final determination.

Regulation	Requirement	AxonFlow Capability
HIPAA 164.312(a)	Access control — unique user identification, emergency access procedure, automatic logoff, encryption.	Per-decision audit records can include authenticated identity from the configured identity path. Policy enforcement gates access at runtime. External TLS termination, internal transport, database encryption, and credential encryption depend on the deployment architecture and configuration.
HIPAA 164.312(b)	Audit controls — record and examine activity in systems containing ePHI.	Every policy decision produces a structured audit record with `decision_id`, `verdict` (allow/deny/redact/escalate), `identity`, `timestamp`, and `policy_id`. Records are queryable via API and exportable as evidence packages.
HIPAA 164.312(e)	Transmission security — guard against unauthorized access to ePHI during transmission.	Configurable PII controls can identify and redact supported sensitive identifiers before selected LLM or tool paths. Deployers remain responsible for approved TLS, network, model-provider, and connector paths.
HITECH Act	Breach notification — notify affected individuals and HHS when unsecured PHI is disclosed.	PII controls can reduce disclosure risk, while decision records support incident investigation. The covered entity or business associate remains responsible for breach assessment, notification decisions, and evidence beyond AxonFlow's recorded fields.
FDA AI/ML SaMD	Predetermined change control plan, performance monitoring, and transparency for AI/ML-based software as a medical device.	Policy versioning and decision records can support change-control and monitoring evidence. Circuit-breaker controls can block new governed requests after configured thresholds trip; AxonFlow does not perform clinical performance validation.
EU MDR	Post-market surveillance, clinical evaluation, and risk management for medical devices including AI-based software.	Evidence export produces time-bounded audit packages for post-market surveillance. HITL approval gates enforce human oversight for clinical risk decisions. Circuit breaker addresses risk management.
EU AI Act Art 13–14	Transparency (Art 13) and human oversight (Art 14) requirements for high-risk AI systems.	Decision records can support transparency evidence by recording governed actions and policy outcomes. HITL gates can support human oversight, while the deployer remains responsible for meaningful review, instructions, and the broader Article 14 control design.
GDPR Art 17	Right to erasure — data subjects can request deletion of their personal data.	Erasure API endpoint supports tenant-scoped data deletion requests. Audit records confirm deletion was executed. PII detection reduces the surface area of stored personal data.

Trust & Rollout

Controls reviewers can inspect before production

AxonFlow is not a compliance certification product. It provides runtime controls, audit evidence, deployment choices, and human approval paths that security, legal, and platform teams can review before AI reaches sensitive workflows.

Control-first Trust Center: security features, data handling, telemetry posture, and current certification status are documented clearly.
Evaluation path: teams can validate approval queues, policy simulation, and evidence workflows before committing to production rollout.
Enterprise path: design partners can work with AxonFlow on deployment shape, procurement review, and regulated workflow rollout.

Review Trust Center Start Evaluation

Govern AI agents handling patient data