AI tool adoption with compliance guardrails, not shadow IT.
Policies, risk assessment, and Copilot and LLM governance under the same accountable team as security and cloud.
Mandry Technology provides AI governance and security services for compliance-driven organizations in Texas and adjacent states: AI adoption policies and guardrails, tool intake and risk assessment, Microsoft Copilot and LLM governance, and PHI and data-handling scoping for regulated workloads. AI Governance governs how new tools enter the environment under the same controls, documentation standards, and accountability chain as Cybersecurity, Managed IT, Cloud, and Unified Communications, with controls and documentation mapped to HIPAA, FERPA, GLBA, and NIST AI RMF. Scope is customized during assessment; engagements can include full policy development or integration with existing compliance programs.
What's included in Mandry AI governance and security.
AI adoption policies, tool governance, and audit-ready documentation under one accountable team. Scope is customized during assessment; this is the baseline for regulated environments.
AI adoption policy library aligned to your regulatory obligations
Tool intake and risk assessment workflow for new AI services
Microsoft Copilot and Microsoft 365 AI governance
LLM and third-party AI vendor review and approval
PHI and PII data-handling scoping for AI workloads
Staff use guidelines and training for approved AI tools
Integration with cybersecurity controls and identity policies
Compliance documentation program for audits and examinations
AI usage observability and monitoring across approved tools
AI adoption planning and roadmapping
Capabilities
What Mandry operates, not what gets forwarded to a vendor.
AI Governance & Security at Mandry means accountable operations with documentation that holds up under audit, not a menu of third-party referrals.
AI adoption policies
Policy library covering approved use cases, prohibited data classes, vendor requirements, and escalation paths for new tool requests. Policies designed for regulated environments where shadow AI adoption is both an operational risk and an examination finding.
Tool risk assessment
Structured intake and risk assessment for Copilot, LLMs, automation platforms, and third-party AI services before they reach production. Assessments document data flows, subprocessor relationships, and control gaps examiners and carriers request.
Copilot and Microsoft 365 AI governance
Tenant configuration, data boundary scoping, and access controls for Microsoft Copilot and M365 AI features integrated with the cloud practice. Copilot deployed with the same documentation standards as the rest of your Microsoft 365 environment, not enabled by default without a compliance review.
LLM and vendor governance
Third-party LLM evaluation, BAA and subprocessor review, and approval workflows for AI vendors entering your environment. Vendor governance that produces the documentation HIPAA auditors and FFIEC examiners request, not a one-page vendor checklist.
PHI and data-handling scoping
Data-class mapping for AI workloads: what PHI, PII, and regulated data can enter which tools, under what conditions, and with what retention boundaries. Scoping designed to hold up when an auditor asks what your staff can paste into an LLM.
Compliance documentation
AI governance posture assessments, policy libraries, tool approval records, training documentation, and evidence binders maintained continuously. The documentation cyber insurance carriers and auditors request when AI tools are part of your operating environment.
Framework Mapping
How ai governance & security maps to the frameworks you answer to.
Compliance buyers need to know which security controls touch which obligations. This is the crosswalk auditors, carriers, and compliance officers look for before they ask for evidence.
The difference shows up when an audit, breach, or carrier renewal forces you to produce evidence, not when everything is running smoothly.
When it matters
Generic AI consultant
Mandry
Regulatory literacy
"We help with compliance" without framework-specific controls
Controls and documentation mapped to HIPAA, FFIEC, FERPA, TX-RAMP, and GLBA
Vendor coordination
Five separate vendor relationships to manage
One accountable team across all five practices
Audit evidence
Incident tickets and ad hoc reports
Continuous attestation, documentation program, and evidence binders
AI-era threats
Generic phishing filters and annual training
Voice-cloning protocols, AI tool governance, and SOC tuned for generative threats
Trust
The evidence underneath the claim.
SOC 2 Type II
Type II attestation
24/7 help desk
help desk and SOC coverage
97%
client retention
20+
years of continuous operation
Scenario
What happens when a healthcare organization enables Microsoft Copilot without scoping PHI data flows.
Copilot can surface content from email, SharePoint, and Teams based on user permissions. For a HIPAA-covered entity, enabling it without data-class scoping means clinical notes, patient identifiers, and billing data may enter Microsoft's AI processing pipeline before anyone documents the BAA chain or access boundaries. Mandry maps data classes before Copilot rollout, configures tenant boundaries aligned to HIPAA requirements, and maintains AI governance documentation continuously. The IT director gets Copilot deployed on a realistic timeline; the compliance officer gets evidence that holds up when an auditor asks what staff can access and what gets sent to AI services.
Memberships
HCISPP
Vendor Stack
Related Practices
How ai governance & security connects to the practice stack.
Mandry operates five practices under one accountable team. Explore the related practices that extend this foundation.
AI governance and security at Mandry is the adoption layer for compliance-driven organizations: AI adoption policies, tool risk assessment, Copilot and LLM governance, and PHI data-handling scoping under the same accountable team that manages IT, security, and cloud. Controls and documentation are designed to hold up under HIPAA, FERPA, GLBA, and NIST AI RMF examinations rather than generic AI readiness checklists.
How does Mandry govern Microsoft Copilot and M365 AI?
Copilot and M365 AI features are configured with tenant boundaries, data-class scoping, and access controls integrated with the cloud practice. Rollout includes a compliance review of what content Copilot can access, BAA and subprocessor documentation, and staff use guidelines before production enablement. Copilot is governed as part of your Microsoft 365 environment, not deployed as a standalone productivity experiment.
How does Mandry scope PHI and regulated data for AI tools?
Data-class mapping documents what PHI, PII, and regulated data can enter which AI tools, under what conditions, and with what retention boundaries. Scoping aligns to HIPAA minimum necessary principles, FERPA student data protections, and GLBA financial data requirements. The goal is documented boundaries examiners can verify, not a blanket ban that staff work around through shadow IT.
How does AI governance relate to cybersecurity at Mandry?
Cybersecurity is the security anchor; AI Governance extends that discipline to how new tools enter the environment. Identity controls, data loss prevention, and SOC monitoring from cybersecurity integrate with AI tool approval workflows and staff training. When voice cloning and generative phishing are operational threats, governing what AI tools staff deploy is part of the same security posture.
How does Mandry evaluate third-party LLMs and AI vendors?
Third-party AI services go through structured risk assessment: data flows, subprocessor relationships, BAA requirements, and control gaps documented before approval. Vendor evaluation produces the records HIPAA auditors and cyber insurance carriers request, not a signed terms-of-service checkbox. Approved vendors are tracked in the compliance documentation program alongside other subprocessors.
What audit evidence does Mandry produce for AI governance?
AI governance posture assessments, adoption policy libraries, tool approval records, training documentation, data-handling scoping records, and evidence binders maintained continuously for HIPAA, FERPA, GLBA, and NIST AI RMF examinations. Mandry's own SOC 2 Type II attestation evidences the operating discipline clients inherit. Evidence is produced continuously, not assembled when an auditor asks what AI tools your staff are using.
Choosing a managed IT services company is itself a compliance-visible decision.
The right time to evaluate one is before the audit, before the breach, before the regulator's letter arrives.
