AI adoption fails audits - and public trust - when no one can show how a system decides, what data it touched, or who's accountable. ALINEDS helps government and regulated organizations govern AI end to end: risk assessment, security controls, human oversight, and compliance mapped to the NIST AI Risk Management Framework. We put the guardrails, documentation, and monitoring around your AI so you can deploy it confidently, prove it's under control, and keep it that way as models and regulations change.
Why it matters
For a government or regulated organization, an ungoverned AI system is a liability waiting to surface - in an audit, a records request, or a headline. Regulators, boards, and constituents increasingly expect to see how AI decisions are made and controlled. Governance is what lets you adopt AI without inheriting unmanaged risk, and it's often the difference between a pilot that stalls in review and one that reaches production.
What you get
AI risk assessment
We identify and rate the risks in your AI use cases - accuracy, bias, security, privacy, and misuse - so you know what you're managing before you deploy.
Governance framework & policies
We establish the policies, roles, and decision gates (who approves what, when a human must intervene) that keep AI use accountable.
Security controls for AI
We secure the data, models, and pipelines against leakage, prompt injection, and unauthorized access, with audit logging throughout.
Compliance mapping
We map your AI controls to the NIST AI RMF and your existing obligations (NIST 800-53, HIPAA, FERPA), so governance and compliance are one effort.
Human oversight & monitoring
We build in human-in-the-loop checkpoints and ongoing monitoring so AI behavior stays within policy over time.
Documentation & audit readiness
We produce the model, data, and decision documentation regulators and leadership ask for.
How it works
Assess
Inventory your AI use cases and assess their risk, data, and exposure.
Govern
Define policies, roles, oversight gates, and acceptable-use boundaries.
Secure
Implement security and privacy controls across data, models, and pipelines.
Monitor
Put ongoing monitoring, review, and documentation in place to sustain control.
Solution offerings
Where it fits
AI adoption review board
Stand up the process that vets and approves AI use cases before they go live, so nothing ships ungoverned.
Securing a generative AI / RAG deployment
Wrap governance and security controls around an LLM/RAG system handling sensitive records.
Vendor AI risk assessment
Evaluate third-party AI tools and models for security, privacy, and compliance before procurement.
Audit & records readiness
Assemble the documentation and controls needed to answer an auditor or a public-records request about an AI system.
Key distinctions
Governed AI vs. ungoverned AI
| Aspect | Governed AI | Ungoverned AI |
|---|---|---|
| Accountability | Defined owners and oversight gates | Unclear who's responsible |
| Data protection | Controlled, logged, least-privilege | Sensitive data at risk of leakage |
| Compliance | Mapped to NIST AI RMF & your mandates | Unmapped, audit-exposed |
| Decisions | Documented and reviewable | Opaque "black box" |
| Change | Monitored as models/rules evolve | Drifts out of control |
Compliance & security
Governed, documented, and audit-ready
Our AI governance work aligns your controls to the NIST AI Risk Management Framework and integrates with the standards you already answer to - NIST 800-53, NIST CSF 2.0, HIPAA, FERPA, and GovRAMP. NIST AI RMF is an alignment target we help you meet, not a certification ALINEDS holds. Security controls cover the data, models, and pipelines behind your AI, with audit logging throughout.
- NIST AI RMF
- NIST 800-53
- NIST CSF 2.0
- FedRAMP
- GovRAMP
- HIPAA
- FERPA
Key terms
- NIST AI Risk Management Framework (AI RMF)
- A voluntary NIST framework for identifying and managing AI risks across four functions - Govern, Map, Measure, and Manage.
- AI governance
- The policies, roles, and controls that keep an organization's AI use accountable, secure, and compliant.
- Human-in-the-loop
- A design where a person reviews or approves an AI system's output at defined decision points, rather than letting it act fully autonomously.
Frequently asked
What does "AI governance" actually mean?
It's the set of policies, roles, and controls that keep your AI use accountable, secure, and compliant - deciding who approves what, how AI decisions are documented, where a human must stay in the loop, and how the system is monitored over time.
Do we need AI governance if we're just running a small pilot?
Yes, at a proportional level. Even a pilot touches real data and sets precedents. Lightweight governance early prevents a pilot from stalling in review and shortens the path to production.
What is the NIST AI RMF and do you align to it?
The NIST AI Risk Management Framework is a voluntary federal framework for managing AI risk across four functions - Govern, Map, Measure, and Manage. We use it as the alignment target for your AI controls; it's a framework we help you meet, not a certification we hold.
How do you secure an AI system differently from regular IT?
AI adds new attack surfaces - training and prompt data, the model itself, and risks like prompt injection or data leakage into public models. We secure the data, models, and pipelines for those risks, on top of standard IT controls.
Can you govern AI tools we bought from a vendor?
Yes. We assess third-party AI tools and models for security, privacy, and compliance, and put the oversight and documentation around them so their use meets your obligations.
Who needs to be involved from our side?
Typically a mix of IT/security, compliance or legal, and the business owner of the AI use case. We help you stand up a lightweight review process so those roles have clear decision points.
How is this different from your Generative AI & LLM service?
Governance wraps controls, oversight, and compliance around AI; the Generative AI & LLM service builds the RAG system itself. They're complementary - most teams need both.