Value Thread Audit · 3–4 Weeks · $15–40K

Find the value thread in your data, BI, and AI spend.

You've invested in data infrastructure, BI tooling, and AI experiments. You can't say with confidence what each dollar produced. We map the entire value chain — what you have, what it's worth, where it leaks — and hand you a 90-day plan to fix the gaps.

Three patterns we keep finding

If two of these sound familiar, the audit will likely pay for itself in the first redirected line item.

You can't trace which dollar produced which dollar.

Data platform, BI suite, AI tooling, three pilots — and no shared way to attribute outcome value to specific investments. Each tool's vendor reports its own ROI; nobody reports the system's.

Your data is rich, your BI is shallow, your AI is stuck in pilot.

You have the raw asset and the dashboards. The AI initiatives keep stalling on data shape, semantic gaps, or privacy guardrails that nobody fully understands.

Privacy and regulatory exposure is blocking real workloads.

There are use cases you cannot ship because of where the data lives, what it contains, or which jurisdictions it touches. Counsel says no; nobody has offered a technical alternative.

What you get

Value-chain map: data sources → BI surfaces → AI workloads → business outcomes, with confidence intervals on each arrow
AI/BI/data spend attribution: which line items produced which measurable outcomes
Privacy-enhancing tech (PET) fit analysis: where DP, FHE, MPC, federated learning, or secure enclaves would unlock blocked workloads
Open-weight model deployment options for your specific data and infrastructure
Gap analysis prioritized by business impact and effort
90-day plan with named owners, milestones, and acceptance criteria
Executive read-out deck for your board or sponsor

How the engagement runs

Fixed scope, fixed timeline, fixed price. No scope creep built in.

WEEK 1

Scoping & discovery

Stakeholder interviews, inventory of data platforms, BI tools, AI projects in flight, and current spend lines. Establish what 'value' means in your context — top-line, cost, risk, time-to-decision.

WEEKS 2–3

Value-chain mapping & PET analysis

Build the data → BI → AI → outcome map. Identify where attribution exists, where it doesn't, and where privacy-enhancing technology would unlock blocked use cases. Pressure-test with your teams.

WEEK 4

Read-out & 90-day plan

Findings deck, prioritized gap list, 90-day execution plan with owners and milestones. Working session with sponsors to align on next steps — with or without our continued involvement.

Scope & pricing

Compact

$15K
3 weeks

Single business unit, up to 5 data sources, 2 AI initiatives reviewed

  • Value-chain map (scoped)
  • Gap analysis with top 5 recommendations
  • 90-day plan
  • Executive read-out
Most Common

Standard

$25K
4 weeks

Multi-BU, up to 15 data sources, 5 AI initiatives reviewed

  • Full value-chain map with attribution analysis
  • PET fit analysis across blocked use cases
  • Gap analysis with prioritized roadmap
  • 90-day plan and quarterly milestones
  • Two read-out sessions (sponsor + board)

Enterprise

$40K
4 weeks + 2 implementation

Org-wide, unlimited data sources, full AI portfolio review

  • Everything in Standard
  • Privacy-enhancing tech proof-of-concept for one blocked workload
  • Open-weight model deployment recommendation with sizing
  • Two implementation weeks (paired with your team)
  • 30 days of post-engagement Slack/email support

What's different about this audit

Most AI consulting work either (a) maps to a generic “maturity model” with the same advice for every client, or (b) sells you the consulting firm's preferred vendor stack. Neither tells you which dollar you already spent produced which dollar of outcome.

We work backwards from outcomes. Where attribution is missing, we say so explicitly. Where privacy or regulatory exposure is the actual blocker, we recommend the specific privacy-enhancing technology (differential privacy, homomorphic encryption, federated learning, secure enclaves, zero-knowledge proofs) that unlocks the workload — not a vague “governance framework.”

And we don't sell you anyone else's software. The engagement ends with a plan your team can execute, on infrastructure you already own, with open-weight models you control.

Frequently asked questions

What exactly is an AI value thread audit?

A 3–4 week engagement that traces your existing data infrastructure → BI tooling → AI experiments → business outcomes, identifying where value is being created, where it's leaking, and where attribution is missing. The output is a value map, a gap analysis, and a prioritized 90-day plan you can execute with or without us.

Who is this for?

Mid-market and enterprise organizations that have spent meaningful dollars on data infrastructure, BI tools, and AI experiments — typically $500K+ in annual AI/data tooling spend — but cannot confidently answer: which of those dollars produced measurable business outcomes? PE-backed portfolio companies are a particularly good fit.

How is this different from a McKinsey or BCG engagement?

Three differences: (1) Fixed scope, fixed price, 3–4 weeks — not a six-month strategy deck. (2) Delivered by senior practitioners, not junior associates. (3) We map to specific privacy-enhancing technologies (differential privacy, homomorphic encryption, federated learning, secure enclaves) where they actually reduce your data risk, rather than vague 'governance frameworks.'

What happens to our data during the audit?

Your data does not leave your environment. We operate under your existing access controls; if needed, we work with synthetic or differentially-private projections of sensitive datasets. The audit produces a value map of your AI/BI/data spend, not a copy of your data.

Do we need agents deployed to engage you?

No. The value thread audit is the upstream offering — it works whether you have zero agents, dozens of LLM-based workflows, or a mix of BI and predictive ML. If you already have agents in production and need vendor-by-vendor evaluation, our AI Agent Capability Audit is the natural follow-on.

What if our biggest issue is privacy or regulatory exposure rather than ROI?

The audit explicitly evaluates privacy-enhancing technology fit (PET) — when differential privacy, homomorphic encryption, federated learning, or secure enclaves would let you unlock data assets that are currently off-limits. This is a core differentiator: most consulting firms don't have hands-on PET expertise.

Find your value thread.

30-minute scoping call. We'll walk through your current data/BI/AI footprint and tell you which tier fits — or that the audit isn't the right next step.