Book a call
Portfolio Services · PE Funds

Your portfolio has
8 manufacturing companies.

Two of them have
an AI opportunity worth acting on.

A 6-week structured engagement: every manufacturing portfolio company screened on operational data, top candidates assessed on-site, investment-committee memos for the 2–3 viable opportunities — with EBITDA impact range, investment required, and a clear recommendation.

Book a 30-minute call → No commitment · Honest answer even if the answer is no
PhD Physics · CERN Researcher · Six Sigma · 15y Boston Scientific · EMEA Analytics · Industrial AI
What the output looks like
Portfolio Screening · 6 Companies Week 2 deliverable
01
Mfg Co. C Visual Inspection · CNC line
●●●
02
Mfg Co. A Predictive Maintenance · Press
●●●
03
Mfg Co. F Yield Optimization · Injection
●●○
Mfg Co. B No viable use case identified
○○○
Mfg Co. D Insufficient process data
○○○
Mfg Co. E Out of scope · Regulated process
○○○
IC memo
Business Case Memo · Priority 01
Mfg Co. C — Visual Inspection
Use Case Automated defect detection
CNC stamped components, end-of-line
Current Quality Cost €210K / yr
1.4% of revenue · measured from data
Expected AI Recovery €165–230K / yr
Base case: €195K · 3 scenarios modelled
Investment Required €34K one-time
Hardware + deployment. No annual licence.
Payback 6–9 months
Confidence HIGH  ●●●
Recommendation ▶ PROCEED

Illustrative · Anonymized · All values based on comparable deployments

How the engagement runs
Phase 01 · Weeks 1–2 · Screening

All companies, data only

Operational data analysis for every manufacturing company in the portfolio — no site visits required. We screen for quality cost exposure, process variance, and AI use case fit.

You provide: Revenue, OEE, quality cost %, product categories — one data pack per company.

Output: Ranked heatmap. Which companies have viable opportunities and why.
Phase 02 · Weeks 3–4 · Assessment

Top candidates, on-site

One to two days per site on the 2–3 priority companies. Process walkthrough, equipment audit, data infrastructure review. Operator and quality manager interviews.

You arrange: Site access and 4 hours of operator time per visit.

Output: Validated opportunity definition. Risks and data gaps flagged before budget is committed.
Phase 03 · Weeks 5–6 · Business Cases

Investment committee memos

One structured memo per viable opportunity, formatted for your IC. EBITDA impact range, investment required, payback, build/buy/partner recommendation — with the evidence behind each number.

You receive: A decision, not a recommendation to explore further. If the return does not justify the investment, that is what the memo says.
What each business case contains
01

Measured baseline

The current cost of the problem — quality escape rate, unplanned downtime hours, yield loss — quantified from actual operational data, not management estimates. This is the number the AI impact is measured against.

Source → operational data, not interviews
02

Use case definition

The specific AI application scoped to the actual process: which production line, which defect type or failure mode, which data source drives the model. Concrete enough to brief a vendor or an implementation team.

Specificity → line-level, not plant-level
03

EBITDA impact range

Low, base, and high case estimates with assumptions stated explicitly. Conservative by design — we prefer to be confirmed than to oversell. Each scenario is traceable to the baseline measurement.

Format → three scenarios, stated assumptions
04

Investment and payback

Hardware, deployment, and Year 1 opex — itemized and based on comparable deployments, not catalogue prices. Payback calculated from the base case EBITDA recovery. No hidden integration costs.

Basis → comparable deployments, not vendor quotes
05

Go / No-go recommendation

An explicit recommendation with the evidence behind it. Proceed, do not proceed, or a stated prerequisite (typically: a data infrastructure investment that unlocks the opportunity). No ambiguity about what the assessment concluded.

Output → a decision, not a framework

This is not an AI strategy engagement. We do not produce transformation roadmaps, maturity scores, or capability gap analyses. The output is a ranked list of investment decisions, each supported by evidence from your actual portfolio data. Companies without a viable opportunity at acceptable return appear in the output too — with the reasoning.

The analysis is technically grounded because we have built the systems we are evaluating: anomaly detection on production lines, predictive maintenance on process data, computer vision on discrete components. The assessment is not framework-based. It is evidence-based. Fixed-price engagement · Scope agreed before we start · No open-ended billing

Manufacturing companies in your portfolio leaving margin on the table?

A 30-minute call to understand your portfolio and whether the engagement makes sense. No commitment. No proposal before we have understood the situation.

Book 30 minutes → Or write directly
Giulio Piana Founder and Principal · RE:MARK giulio.piana@brandcraft.it