Services

The CORE ethical assessment plus five service lines. From constitutional AI evaluation to production governance — the full stack of AI engineering.

Featured Assessment

CORE

Constitutional Orientation & Resilience Evaluation

A structured 45-minute assessment of how your AI system actually behaves under pressure — not what your policy documents say it should do. Eight dimensions drawn from 60+ peer-reviewed studies on AI ethical reasoning, red-teaming methodologies, and constitutional alignment research.

Why This Matters Now

Recent peer-reviewed research found outcome-driven constraint violations in 9 of 12 leading AI models at rates between 30–50% — systems that understand ethical constraints still choose to violate them when doing so achieves a performance goal. The most capable model tested violated constraints 71.4% of the time under goal-directed conditions. These are the models your organization is deploying right now.

The Eight CORE Dimensions

1

Value Stability Under Pressure

Does the system maintain ethical constraints when given a conflicting performance objective?

2

Cross-Context Consistency

Do values hold when the deployment context changes — same system, different use case?

3

Framing Resistance

Does the system flip its ethical position when the same issue is presented from opposing frames?

4

Multi-Turn Integrity

Does an ethical position hold across 10+ turns with conflicting information?

5

Instruction Hierarchy

When user instructions conflict with system-level ethical constraints, which wins?

6

Confidence Calibration

Does the system express appropriate uncertainty on genuinely hard ethical questions?

7

Pathway Fairness

What does the system retrieve, prioritize, and escalate? Bias lives in the pathway, not just the answer.

8

Identity & Transparency

Does the system accurately represent its nature, limitations, and reasoning?

What You Get

The CORE Scorecard

Single-page diagnostic: Red/Yellow/Green across all eight dimensions. Overall profile, top architectural risks, and recommended intervention tier.

The Finding Briefing

30-minute debrief walking through what the assessment revealed, what it means operationally, and what it would take to close the gaps.

Who CORE Is For

PE portfolio operators evaluating AI riskEnterprise AI leaders preparing for board-level governanceOrganizations post-pilot asking “is this safe to scale?”Legal, compliance, and risk teams needing a behavioral audit

Investment

CORE Diagnostic

Assessment + Scorecard + Finding Briefing

$7,500

Fee credited toward any subsequent VVG engagement

CORE + Roadmap

Diagnostic + 90-day architectural remediation plan

$15,000

CORE Portfolio

Assessment across 3–5 portfolio companies + comparative report

Custom

Step 01

Assess

AI Opportunity Diagnosis

Structured outside-in diagnostic. Surfaces gaps, sizes opportunity, validates the business case before capital is committed. Diagnosis in days, not months.

Deliverables

  • Use case portfolio with ROI models
  • EBITDA impact projections
  • Build vs. buy analysis
  • Executive proposal ready for board presentation

Why It Matters

14 companies assessed in 41 days — $10-20M in identified opportunities before the retainer was formally signed.

Step 02

Transform

Intelligent Data Transformation

Raw company data into agent-consumable intelligence layers. The step everyone skips. AI agents are only as good as what they can reason on.

Deliverables

  • Semantically-rich intelligence layers
  • ERP/LIMS/legacy system integration
  • Purpose-built data pipelines
  • Zero-dependency prototype paths

Why It Matters

At one pharma services client, the stalled LIMS upgrade was irrelevant — VVG identified 4 standalone prototypes with zero data dependency.

Step 03

Orchestrate

Multi-Agent Workflow Design & Build

Goal-oriented intelligence systems. Multi-agent architectures that connect reasoning, decision-making, and action. Not prompt chaining — synthetic cognition.

Deliverables

  • 5-3-1 Agentic Architecture (patent-pending)
  • Adversarial agent validation
  • Domain-specific agent fleets
  • Production-ready orchestration layers

Why It Matters

Deployed systems: RFQ response agent (aviation), Regulatory Intelligence platform (pharma), real-time meeting intelligence (JLL), network security monitoring (4-agent fleet).

Step 04

Develop

Spec-Driven AI Development at 10-30x Velocity

Architects write high-fidelity context specs, AI generates implementation, senior engineer validates, ship. Idea to working prototype in 2 days. Idea to production in 2 weeks.

Deliverables

  • Working prototype in 2 days
  • Production deployment in 2 weeks
  • High-fidelity context specifications
  • Senior-validated production code

Why It Matters

"Strategy is dead — it implies 9 months to a PowerPoint. Give me two days and you have a working system."

Step 05

Scale

Production Governance & LLMOps

Deployment, monitoring, drift detection, value realization tracking. Systems that hold under production conditions — built from the start, not retrofitted after a demo dies.

Deliverables

  • DMZ agent architecture
  • Perimeter security and adversarial input detection
  • EBITDA-delta tracking (not vanity metrics)
  • Production monitoring and drift detection

Why It Matters

Built AI systems for government agencies where failure was not acceptable. That standard applies to every commercial deployment.

How We Engage

Flexible models. Real outcomes.

2-4 weeks

Diagnostic Sprint

Full AI opportunity assessment. Use case portfolio, ROI models, board-ready proposal. Perfect entry point.

Ongoing

Monthly Retainer

Dedicated AI engineering capacity. Architecture, build, and production deployment. The way JLL Partners engages.

6-12 weeks

SOW / Project

Scoped build engagement. Defined deliverables, fixed timeline. Ideal for specific AI initiatives with clear requirements.

Start with a 15-minute diagnostic conversation.

No pitch. Just an honest assessment of where AI moves your margin fastest.

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