What FedRAMP Means for Enterprise AI Vendors

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"Are you FedRAMP authorized?"

This question—once limited to government procurement—now comes from enterprise buyers across regulated industries. FedRAMP has become shorthand for "serious about security."

For AI vendors, FedRAMP authorization is a major barrier. For enterprise buyers, understanding FedRAMP helps evaluate AI vendor security claims.

What FedRAMP Is

The Federal Risk and Authorization Management Program (FedRAMP) is the US government's framework for security assessment of cloud services.

Key elements:

  • Standardized security requirements based on NIST SP 800-53
  • Independent third-party assessment
  • Continuous monitoring requirements
  • Reciprocity across government agencies (authorize once, use anywhere)

Authorization levels:

  • Low: Public data systems
  • Moderate: Most government data
  • High: High-impact data, law enforcement, critical infrastructure

Most enterprise-relevant authorizations are Moderate or High.

Why FedRAMP Matters Beyond Government

FedRAMP authorization signals:

Proven security controls: 300+ controls verified by independent assessors Continuous monitoring: Not just point-in-time compliance Incident response: Defined procedures and government notification requirements Documented architecture: Boundary definitions, data flows, security measures

For enterprises in regulated industries—healthcare, financial services, critical infrastructure—FedRAMP authorization provides assurance that's otherwise expensive to verify independently.

The AI Vendor Challenge

Most AI vendors aren't FedRAMP authorized:

Timeline: Initial authorization typically takes 12-18 months Cost: $500K-$2M+ for the authorization process Resources: Requires dedicated compliance team and significant engineering effort Ongoing burden: Continuous monitoring, annual assessments, POA&M management

Frontier AI companies have been focused on capability development, not compliance infrastructure. The result: a gap between enterprise needs and AI vendor readiness.

The Current State of AI FedRAMP

As of 2026:

Major cloud platforms: AWS, Azure, GCP all have FedRAMP High authorizations AI services on those platforms: Limited FedRAMP coverage

  • Azure OpenAI: Available in some FedRAMP regions
  • AWS Bedrock: Available in GovCloud
  • Google Cloud AI: Limited availability

Standalone AI vendors: Most are not FedRAMP authorized

This creates a procurement challenge: cloud infrastructure is compliant, but AI services running on it may not be.

Options for Enterprise Buyers

Option 1: Wait for Vendor Authorization

Approach: Only use AI vendors with FedRAMP authorization

Reality: Limited options, especially for specialized capabilities. May wait years for vendors to complete authorization.

Best for: Government agencies with hard FedRAMP mandates

Option 2: Use FedRAMP-Authorized Infrastructure

Approach: Deploy AI on FedRAMP-authorized cloud infrastructure (Azure, AWS GovCloud)

Reality: You can run models on authorized infrastructure, but:

  • Open models must be self-managed
  • Proprietary vendor models (OpenAI, Anthropic) may not be available in authorized regions
  • You inherit operational responsibility

Best for: Enterprises with cloud operations capability

Option 3: On-Premise Deployment

Approach: Deploy AI entirely within your own authorized environment

Reality: Your data center is under your authorization boundary. AI running there inherits your compliance posture.

Benefits:

  • No dependence on vendor FedRAMP status
  • Full control over security configuration
  • Often faster than waiting for vendor authorization

Best for: Enterprises with existing on-premise infrastructure or strict data residency requirements

Option 4: Accept Risk with Mitigations

Approach: Use non-authorized AI services with compensating controls

Reality: May be acceptable for some use cases with appropriate risk acceptance

Mitigations:

  • Data classification ensuring only low-sensitivity data goes to AI
  • Contractual protections
  • Additional monitoring and logging

Best for: Non-government enterprises where FedRAMP isn't mandatory

The On-Premise Path

For many enterprises, on-premise AI deployment sidesteps the FedRAMP vendor problem:

How it works:

  • Open models (Llama, Mistral) run on your hardware
  • Knowledge graphs and data stay within your boundary
  • Your existing authorization covers AI operations

Requirements:

  • Infrastructure for AI workloads (GPU compute)
  • Operations capability (or managed service provider within your boundary)
  • Model management and update processes

Advantages:

  • No waiting for vendor authorization
  • No third-party data access
  • Full control and visibility

This is why many government contractors and regulated enterprises choose on-premise for sensitive AI workloads.

What to Ask AI Vendors

When evaluating AI vendors for regulated environments:

  1. What's your FedRAMP status?

    • Authorized (which level?)
    • In process (with which agency sponsor?)
    • Planning to pursue (timeline?)
    • No plans (why not?)

  2. What security certifications do you have?

    • SOC 2 Type II
    • ISO 27001
    • Other relevant certifications

  3. Can you deploy on-premise or in our environment?

    • Within our FedRAMP boundary
    • In our data center
    • In our cloud tenant

  4. What data do you process and where?

    • Geographic location of processing
    • Subprocessors involved
    • Data retention and deletion

  5. Can you provide penetration test results and architecture documentation?

    • Independent security assessments
    • Boundary diagrams
    • Data flow documentation

For AI Vendors: The Path Forward

If you're an AI vendor serving regulated enterprises:

Short term: Document your security posture

  • Complete SOC 2 Type II
  • Develop thorough security documentation
  • Be transparent about what you have and don't have

Medium term: Enable on-premise deployment

  • Many customers will self-host if you can't meet their compliance needs
  • On-premise option expands addressable market
  • Removes you as the compliance bottleneck

Long term: Pursue FedRAMP

  • Find an agency sponsor
  • Begin authorization process
  • Plan for 12-18 month timeline

The vendors who solve the compliance problem early will capture the regulated enterprise market.

The Phyvant Approach

Phyvant is designed for this reality:

On-premise deployment: The knowledge layer runs entirely within your environment—no data egress, no dependence on our authorization status.

Open model compatibility: Works with any self-hosted open model, giving you model choice within your boundary.

Security documentation: Full architectural documentation, security controls, and implementation guidance for your compliance needs.

For enterprises with FedRAMP requirements, this means you can deploy today without waiting for our authorization. The AI runs in your environment, under your authority.

See how Phyvant deploys within your boundary → Book a call

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