Portfolio AI Program · Private equity
Turn AI into portfolio value. Company by company.
Hikari Blue helps private equity firms identify, engineer, and deploy AI initiatives across their portfolio companies, connecting execution to measurable operating performance.
One disciplined execution approach. Applied to each company's business, systems, and priorities.
A named partner reviews every brief. United States · Switzerland · France.
Investment imperative
Why portfolio AI execution matters now.
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Make AI a contributor to your value creation plan.
AI earns a place in the plan when it moves a measure the fund already tracks. Each initiative is tied to revenue, margin, cash or resilience, with the measure set before work starts.
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Protect portfolio value as AI reshapes competitive advantage.
AI is changing cost structures and customer expectations across sectors. A company that adapts late carries that exposure through the holding period and into the exit.
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Scale what works. Adapt what matters.
What is proven in one company informs the next, with the same method and the same standard of measurement. What is built stays fitted to each company's business, systems and priorities.
According to McKinsey's Global Private Markets Report 2026, operational value creation has become an essential source of private equity returns, and AI is joining the traditional value creation levers.
BCG (2026) observes that few firms have demonstrated significant returns from AI across several portfolio companies; the gap is operational transformation, not access to technology.
Sources: McKinsey, Global Private Markets Report 2026 · opens in a new tab BCG, Inside the AI-first private equity firm (2026) · opens in a new tab
Value creation
AI should be measured in business outcomes, not deployments.
The number of AI pilots is not a measure of value creation. What matters is whether an initiative improves revenue, margins, cash generation, or competitive resilience. Hikari Blue connects technical execution to defined operating objectives, with measurement built into the engagement.
Effects to be demonstrated engagement by engagement, never guaranteed.
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Revenue growth
- What AI can contribute
- Commercial efficiency, conversion, retention.
- Measure to prefer
- Incremental revenue and margin.
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EBITDA improvement
- What AI can contribute
- Automation and process optimization.
- Measure to prefer
- Net EBITDA improvement.
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Cash generation
- What AI can contribute
- Working capital and operations.
- Measure to prefer
- Additional cash flow.
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Operating leverage
- What AI can contribute
- Growth without proportional resources.
- Measure to prefer
- Unit costs and margins.
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Downside protection
- What AI can contribute
- Adaptation to disruption in the company's market.
- Measure to prefer
- Exposure reduced, losses avoided.
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Exit readiness
- What AI can contribute
- Documented processes, reliable systems, verifiable indicators.
- Measure to prefer
- Data quality and readiness for due diligence.
Durable EBITDA improvement is one lever of enterprise value. The multiple, risk, revenue quality, required investment and market conditions remain decisive.
The program
Identify. Execute. Scale.
The method can be replicated. The solution stays specific to the company.
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Identify
Find the highest-value AI opportunities across your portfolio.
Scoped with the fund: which companies, which value creation priorities, which questions to answer. No full audit of every company without that framing.
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Execute
Turn a selected opportunity into a production-ready business capability.
One selected company, with outcomes defined before the build. Success is verified in the processes, in adoption and in the contribution to the agreed objective.
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Scale
Extend proven capabilities across the portfolio.
Never automatic. Each new company is a new mandate, qualified on its own business, systems and priorities before any work starts.
Why Hikari Blue
From investment thesis to operating reality.
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From investment thesis to operating execution.
We start from the value creation plan, not from the technology. Each initiative is tied to an operating objective the fund already tracks, with the measure agreed before the build.
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Built around the business. Not around a model.
Each capability is designed from the company's processes, data and systems. The architecture stays model-agnostic, so the company is not bound to a single model vendor.
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Production AI, with regulated-grade rigor.
A named owner, a trace of every action, a stop available at any moment. This is the standard we hold in every company, not a condition for working with us.
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Work with management. Build capabilities that last.
We work with the company's management and teams, not around them. Documentation, runbooks and trained owners stay with the company when the engagement ends.
Hikari Blue builds the AI operating layer: the components around the models that make them usable, controlled and measurable in a business.
Investment cycle
One program, three moments of the holding period.
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After acquisition
Identify where AI can contribute to the value creation plan in the first months, then select the first company and the first outcome.
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During holding
Execute in the selected company, measure the contribution against the defined objective, and decide on the evidence whether to extend.
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Before exit
Document the improvements, how the capability is operated and what can be transferred, so a buyer can examine them in due diligence.
Hikari Blue is not a transaction advisor, a valuation firm or legal counsel. We work alongside the advisors the fund already retains.
Engagement
One fund. One selected opportunity. Then a decision on the evidence.
The engagement starts with one company and one written outcome. What follows is decided on what that first engagement demonstrates.
Fund level
- Opportunity analysis across the portfolio
- Program design with the operating team
- Support to the fund's operating partners
Company level
- Engineering mandate in the selected company
- Production deployment
- Operation, then handover to the company's teams
The two levels are complementary. Responsibilities, contracts and billing remain distinct between the fund and each company.
Practical questions
What operating partners ask first.
Is this a consulting engagement or an implementation?
An implementation. We frame the opportunity with the fund, then engineer and put the capability into production in the selected company. Recommendations without execution are not the offer.
How do you choose the first company?
With the fund, on the weight of the opportunity in the value creation plan, the state of the company's data and systems, and a management team ready to sponsor the work.
Who contracts: the fund or the portfolio company?
It depends on the level. Work at fund level is contracted with the fund. An engineering mandate is contracted with the company concerned. Responsibilities and billing stay distinct.
How are results measured?
Against the outcome written before the build: the operating measure the fund and management agree on, verified in the processes, in adoption and in the contribution to the objective.
What stays with the company after the engagement?
The capability, the code, the data on the company's infrastructure, the documentation and trained owners. The company runs it without us.
Does this require regulated-sector exposure?
No. The standard applies to any company: a named owner, a trace of every action, a stop available at any moment. It also satisfies the requirements of regulated sectors.
Next step
Bring one portfolio and one question. A named partner answers within one business day, with a session or a reasoned no.
A two-page program overview is being prepared for operating partners.