AI Security & Governance Practice

Your Organization is Already Using AI.
Is It Secure and Governed?

Employees are using AI tools today — sanctioned or not. Sensitive data is moving. Governance is absent. TWE helps organizations at every stage of AI adoption build the security and governance foundation to move forward with confidence.

CSA AICM v1.0 DAGF v1.0 DASF v2.0 NIST AI RMF ISO 42001 EU AI Act MITRE ATLAS OWASP LLM Top 10
⚠ What we find in every engagement
Shadow AI in active use — Employees using ChatGPT, Copilot, and AI SaaS tools with zero visibility or controls in place
Sensitive data exposed to LLMs — Confidential information entering public models with no DLP policies covering AI traffic
No AI governance program — No acceptable use policy, no AI risk register, no designated AI risk owner or board-level accountability
Ethics and compliance gaps — No AI ethics charter, no bias testing, no regulatory mapping to EU AI Act or NIST AI RMF
AI inference unprotected — LLM interfaces exposed to prompt injection and output manipulation with no guardrails or logging
Compound AI risk unchecked — RAG pipelines and AI agents deployed without retrieval authorization, supply chain vetting, or model integrity controls
243
AICM control objectives — the
governance standard we benchmark against
5
DAGF pillars covering org design,
ethics, compliance, data, and AI security
62
DASF technical AI risks — each
with a mapped mitigation control
3
Maturity tiers — scope calibrated
to your AI adoption level
10+
Mapped standards: MITRE ATLAS,
OWASP LLM Top 10, ISO, HITRUST
30 days
To your first tri-framework scorecard
and prioritized action roadmap
The Challenge
AI is moving faster than your security and governance posture.

Most organizations are deploying AI reactively — chasing productivity gains while leaving critical security, governance, compliance, and ethical gaps exposed across three distinct risk dimensions that no single framework alone addresses.

👁

No AI Visibility

You do not know which AI tools are in use, what data is flowing into them, or who has access to AI-powered platforms. Shadow AI is already active in your environment and your data is already moving.

🏛

No Governance Program

Effective AI governance requires defined roles, board-level accountability, a risk management lifecycle, KPIs, and an AI ethics charter. Most organizations have none of these documented or operational.

🤖

Unprotected AI Systems

LLM inference interfaces, model registries, RAG retrieval pipelines, and agentic workflows carry their own attack surface — one that most security tools and most security consultants were never designed to address.

📋

No Defensible Compliance Baseline

Boards, auditors, regulators, and cyber insurers are asking about AI governance. Without a tri-framework assessment mapped to AICM, DAGF, and DASF, you have no standards-based, defensible answer to give them.

AI Maturity Model
Where do you sit on the AI Adoption Curve?

TWE scopes every engagement to your actual AI maturity level — not a one-size-fits-all assessment that overburdens early adopters or underserves enterprises with complex AI environments. Before any scope is set, our Solutions Architect conducts a structured qualification interview to assign your organization to the correct tier.

Level 1

Early AI Adoption

200 – 500 Employees
Qualification Signals
  • No formal AI governance policy, risk register, or AI risk owner
  • AI limited to one or two SaaS tools (Copilot, ChatGPT Enterprise)
  • No internally developed or fine-tuned models in production
  • No MLOps pipeline or model registry in place
  • Regulatory exposure to AI-specific obligations not yet assessed
Framework Scope
AICM — Quick-ScanGovernance, data security, and identity control domains assessed against 243 control objectives at discovery depth
DAGF — Pillar I OnlyGovernance model identification, policy gap assessment, and AI risk register baseline design
DASF — Discovery TierDeployment model classification, shadow AI discovery, AI supply chain exposure, and top-risk inventory
Recommended: Offering 1 — AI Visibility & Risk Snapshot
Level 2

Active AI Adoption

500 – 1,500 Employees
Qualification Signals
  • AI policy exists but governance program is informal or undocumented
  • Multiple AI tools or platforms across two or more business units
  • At least one internally developed or fine-tuned model in production
  • Basic MLOps practices in place but not formally governed or secured
  • Regulatory obligations emerging: ISO 42001, sector-specific instruments
Framework Scope
AICM — Full AssessmentAll 18 domains, 243 control objectives with full regulatory gap mapping to NIST AI RMF, ISO 42001, EU AI Act
DAGF — All 5 PillarsGovernance design, compliance lifecycle, ethics charter, AI data classification, and AI security program design
DASF — Full AssessmentAll 62 risks across 12 components, FAIR-aligned severity scoring, and control implementation roadmap
Recommended: Offering 2 — AI Readiness Assessment & Roadmap
Level 3

Deep AI Adoption

1,500+ Employees
Qualification Signals
  • Formal AI governance program with executive sponsorship in place
  • Compound AI systems in production: RAG, agentic workflows, multi-model pipelines
  • Production model registry with versioning and RBAC controls
  • Dedicated MLOps pipeline with CI/CD integration for model training and deployment
  • Regulatory obligations specific to AI: EU AI Act high-risk classification, sector instruments
Framework Scope
AICM — Full + Audit PackageAll Level 2 scope plus board-level governance reporting and audit evidence packaging for regulators
DAGF — Full + OperationsAll Level 2 DAGF scope plus AI incident management design, KPI framework, and quarterly pillar review cadence
DASF — Full + Compound AIAll Level 2 DASF scope plus compound AI risk (RAG/agents), MLSecOps pipeline, and adversarial red team exercise
Recommended: Offering 2 + Offering 3 Bundle
Our Offerings
Three offerings. One outcome: AI confidence.

Start where you are. Each offering delivers immediate value and builds toward a secure, governed, AI-ready organization — anchored simultaneously to AICM governance controls, DAGF pillar requirements, and DASF technical risk mitigations.

Offering 1

AI Visibility & Risk Snapshot

Find out what is happening in your environment right now — across governance, data flows, and the AI system layer — in weeks, not months.

1–2 Weeks Fixed Fee All Tiers
AICM — Governance, data security & identity control quick-scan
DAGF — Pillar I governance model & policy gap assessment
DASF — Deployment model classification & top-risk inventory
  • Discover all AI tools in use — sanctioned and unsanctioned — via DNS, proxy, and endpoint telemetry
  • Identify sensitive data categories flowing into AI platforms and public LLMs
  • Assess identity and access controls around AI tool and platform usage
  • DAGF Pillar I quick-scan: governance model, policy gaps, and AI risk register baseline
  • Regulatory quick-check: EU AI Act, NIST AI RMF, and ISO 42001 applicability assessment
  • AI deployment model type inventory: Predictive ML, Foundation Model APIs, External Models
  • Prompt injection and compound AI surface mapping — RAG pipelines and agentic workflows flagged
  • AI supply chain and dependency exposure scan
  • Top 10 risk items ranked by FAIR-aligned severity with business impact narrative
  • 30-day Quick Wins action list and executive briefing deck
Investment: $15,000 – $20,000
Offering 2

AI Readiness Assessment & Roadmap

Full tri-framework assessment — AICM, DAGF, and DASF — with governance program design and a board-ready prioritized action roadmap.

3–5 Weeks Fixed Fee L2 & L3
AICM — Full 18-domain, 243 control-objective assessment
DAGF — All 5 pillars including ethics, compliance lifecycle, and data classification
DASF — All 62 risks across 12 components with FAIR-aligned severity scoring
  • Full 18-domain AICM assessment with control gap mapping and evidence inventory
  • Regulatory gap analysis: NIST AI RMF, ISO 42001, EU AI Act, HIPAA, SOC 2, sector-specific
  • DAGF governance model design: Centralized, Distributed, or Hybrid selection with rationale
  • AI organizational roles, accountability framework, and policy lifecycle design
  • AI ethics charter template, bias testing criteria, and model explainability requirements
  • DAGF AI data classification design: Restricted, Internal, Public with AI usage guidance
  • Six-stage regulatory compliance lifecycle implementation roadmap
  • DASF Risk Heatmap: 12 AI system components, 62 technical risks, FAIR-aligned severity
  • Model registry security, inference guardrail gap assessment, MLOps pipeline security review
  • Compound AI risk analysis: RAG retrieval authorization, agent sandboxing, supply chain (L3)
  • 0–24 month prioritized roadmap across all three framework dimensions
  • Board-ready executive presentation and audit-defensible evidence package
L2: $25,000 – $35,000  |  L3: $35,000 – $50,000
Offering 3

Secure Foundation & Managed Services

Full implementation and ongoing management of your AI security architecture and governance program — from the perimeter to the AI system layer.

60–120 Days Project + Retainer L2 & L3
AICM — Control implementation and operationalization
DAGF — Governance program operationalization and quarterly reviews
DASF — MLSecOps, inference guardrails, model registry, and MLOps hardening
  • Network segmentation, Zero Trust architecture, and AI traffic security controls deployment
  • Identity governance, conditional access policies, and DLP for AI platforms
  • AICM control evidence collection, audit trail design, and board reporting package
  • DAGF governance program operationalization: policies, KPIs, reporting cadences
  • AI incident management program design and tabletop exercise facilitation
  • Quarterly DAGF pillar maturity reviews and board-level AI governance reporting
  • AI inference guardrail deployment and prompt injection defense implementation
  • Model registry RBAC, versioning controls, and lifecycle integrity enforcement
  • AI supply chain security, MLOps hardening, and MLSecOps CI/CD pipeline design
  • AI adversarial red team exercise mapped to MITRE ATLAS (L3 premium add-on)
  • Ongoing managed services with continuous AI security posture monitoring and optimization
From $250–$375/hr + managed services from $8K–$18K/mo
Our Process
From exposure to governed AI in five steps.

A proven, maturity-calibrated methodology that delivers value at every stage — across governance, compliance, and the AI system security layer simultaneously.

🎯

Qualify

A structured discovery interview assigns your organization to the correct maturity tier before any scope is set or any dollar is committed.

👁

Discover

Surface all AI activity, data flows, model deployments, governance gaps, and regulatory obligations across your environment.

📊

Assess

Benchmark simultaneously across AICM governance domains, DAGF program pillars, and DASF technical risk components at your tier scope.

🏗

Build

Design and deploy security architecture and governance programs calibrated to your tier, risk profile, and regulatory environment.

🔄

Manage

Continuously monitor, test, and optimize your AI security posture and governance program maturity — including adversarial testing at L3.

Our Standards
Triple-Framework Coverage: AICM + DAGF + DASF

TWE applies all three complementary frameworks simultaneously. Each operates at a distinct layer — together they produce complete governance, program design, and technical risk coverage that no single framework can provide alone. DAGF explicitly designates DASF as the implementation standard for its AI Security pillar, creating a native framework integration.

Control Taxonomy Layer

CSA AICM v1.0

243 control objectives across 18 governance domains. Maps to NIST AI RMF, ISO 42001, EU AI Act, ISO 27001, and BSI AIC4. The industry-standard AI governance control benchmark.
🏛AI Governance, Risk & Compliance18 Domains
🔒Identity & Access Management243 Controls
📊Data Security & Privacy
🌐Network & Infrastructure Security
📱Application & Interface Security
💾Business Continuity & Resilience
Legal, Regulatory & Ethics Compliance
🔍Audit, Logging & Accountability
Governance Program Layer

Databricks DAGF v1.0

5-pillar AI governance program design framework covering organizational structure, regulatory compliance lifecycle, ethics, data governance, and AI security. Designates DASF as the Pillar V implementation standard.
🏢Pillar I — AI Organizations & Governance5 Pillars
Pillar II — Legal & Regulatory Compliance3 Models
🤝Pillar III — Ethics, Transparency & Interpretability
🖿Pillar IV — Data, AIOps & Infrastructure
🔒Pillar V — AI Security (implemented via DASF)
🕐Governance Models: Centralized / Distributed / Hybrid
📈AI KPI Framework & Performance Monitoring
🚨AI Incident Management Program Design
Technical Security Layer

Databricks DASF v2.0

62 technical risks across 12 AI system components. New in v2.0: compound AI systems, RAG, agents, 7 new risks, 5 new controls. Maps to MITRE ATLAS, OWASP LLM Top 10, NIST AI RMF, ISO 42001, and HITRUST.
🗃Data Sources & Feature Engineering12 Components
🧠Model Training & Evaluation62 Risks
📦Model Registry & Lifecycle Integrity
💬Inference & Runtime Security
🛡Inference Guardrails & Output Filtering
🔗Compound AI: RAG & Agentic Systems (New v2.0)
MLOps Pipeline & CI/CD Security
🏗Platform & AI Supply Chain Security
Why TWE
We don't just advise. We build, govern, and run it.

Most strategy firms hand you a report and move on. TWE has the certified engineers, governance architects, and enterprise partner depth to design, deploy, and manage what we recommend — across the governance layer, the compliance layer, and the AI system security layer simultaneously.

🏆

Enterprise-Certified Specialists

Our engineers hold PCNSE, CCIE, and advanced certifications across our full partner stack. We operate at the enterprise level across security engineering, governance architecture, and AI system design — not at the help desk level.

🕐

Triple-Framework, Standards-Based

Every recommendation maps to a specific AICM control objective, DAGF pillar requirement, or DASF mitigation control. Your gaps are defensible to auditors, regulators, boards, and cyber insurers — not just a consultant's opinion.

🔬

AI System-Layer Security

Beyond perimeter controls, TWE addresses the AI system architecture itself — model registries, inference guardrails, RAG retrieval authorization, supply chain integrity, and MITRE ATLAS-mapped adversarial testing. Most consultants stop at the firewall.

🎯

Maturity-Calibrated Scope

No two clients are at the same stage of AI adoption. Our three-tier maturity model ensures you get the assessment and governance design you actually need — not an over-scoped enterprise engagement delivered to a 300-person organization.

🏛

Governance Program Design Capability

Most security firms cannot design AI governance programs. TWE combines security engineering depth with DAGF governance architecture expertise to deliver both the technical risk assessment and the governance program under a single engagement.

🔄

End-to-End Ownership

From initial risk snapshot through ongoing managed operations and quarterly DAGF governance reviews — one partner, one accountability model, no handoffs to third parties who were not present when the design decisions were made.