01
The AI line in the IC memo can’t be underwritten.
The model assumes AI moves revenue or cost. Nobody on the deal team can say whether the target’s technology, data, and regulatory position will let it.
Private equity
The technology and AI read your deal team doesn’t have.
Independent technology, AI, and regulatory advisory for private-equity sponsors and their portfolio companies, from the pre-LOI quick-look to the next buyer’s diligence. Led personally by Sultan Meghji, former inaugural Chief Innovation Officer of the U.S. FDIC.
Double-digit PE transactions supported in the last three years
Why sponsors call
Four gaps we close.
02
The target’s AI claims can’t be verified from the data room.
Vendor LLM dependencies, model-risk discipline, and training-data provenance rarely show up in the architecture diagram or the SOC 2 report.
03
The portfolio company can’t pass an AI governance audit.
In a bank, insurer, health system, or federal contractor, a use case that can’t survive examination doesn’t ship, and the value-creation line that depended on it doesn’t land.
04
The next buyer will ask questions the company can’t answer.
Model inventory, data lineage, accountability, decision logging. Companies that reconstruct the answers in the data room tell a weaker AI story than the ones that already have them.
Across the deal lifecycle
Six offers, four stages.
Sponsors take them one at a time or in sequence. The team that ran the diligence carries the findings into the 100-day plan, so nothing is lost at close.
-
Stage 01
Pre-deal
Sourcing through signing
1–2 weeks · pre-LOI
AI Thesis Check
A senior read on the two or three technology and AI questions that move the bid, run on whatever the sponsor can secure under NDA.
You get
- Written read on the AI assumptions in the deal model: plausible, bid-protective, or mispriced
- Architecture and risk read on the target
- Ranked list of themes for formal diligence
- Go/no-go input for the deal team
3–6 weeks · post-LOI
Technology & AI Diligence
Formal diligence across eight threads, with an AI overlay built for targets whose value sits in production AI systems.
You get
- Findings across architecture, data and ML, AI and model risk, cybersecurity, third-party risk, engineering organization, and regulatory exposure
- AI overlay: vendor LLM dependency, model-risk discipline, training-data provenance and IP, generative-AI risk surface
- The regulatory exposure new ownership inherits on day one
- An integration thesis: what has to happen post-close, in what order, over what realistic timeline
-
Stage 02
Close & first 100 days
Signing through day 100
First six months post-close
100-Day Technology & AI Plan
Turns the diligence findings into change the portfolio company actually makes, with senior oversight while it happens.
You get
- Sequenced 90/180/365-day plan built from the diligence findings
- A named owner for each integration and AI thread
- Senior oversight one to two days a week for the first six months
- Fractional CIO, CTO, CISO, or Chief AI Officer coverage where the portco needs continuous executive leadership
-
Stage 03
Hold
Across the hold period
Retainer · across the hold
AI Value-Creation Oversight
The independent read for the sponsor on whether the AI thread of the value-creation plan is executable and tracking.
You get
- Value-creation plan review: which AI initiatives stay, which need a governance prerequisite, which come out
- Regular read for the deal team on what is tracking and what isn’t
- Portfolio-company AI governance: model inventory, accountability, board reporting
- Model risk alignment to SR 26-2 for bank portfolio companies
Portfolio-level · quarterly cadence
Portfolio AI Scan
One framework applied across every platform, so the deal team and operating partners get a comparable read instead of bespoke decks.
You get
- Common read on technical risk, AI maturity, regulatory exposure, and integration progress per platform
- Side-by-side view across the portfolio for quarterly reviews
- Exit-readiness sequencing across platforms
- Framework calibrated to the sponsor’s investment thesis, not a generic scoring rubric
-
Stage 04
Exit
12–24 months before sale
12–24 months before sale
AI Exit Readiness Review
The next buyer’s diligence, run early enough to fix what it finds. Oriented to remediation, not assessment.
You get
- Buyer’s-eye read on the technology and AI story the sponsor will tell
- Gap list with a remediation sequence that closes before the process opens
- Model inventory and governance evidence ready for the data room
- The diligence themes the acquirer is likely to land on
How we fit
Alongside your other advisors, not instead of them.
Your quality-of-earnings, financial, and commercial diligence providers answer what the business earns. Virtova answers whether the technology, the AI, and the regulatory position underneath those earnings will hold. We coordinate with the rest of the deal team so the findings land in one place.
Virtova is the consulting side: the read, the plan, and the accountability. The sponsor chooses who builds. Virtova and Frontier Foundry share ownership, and that relationship is disclosed up front.
Who runs it
One senior operator, on every deal.
Sultan Meghji leads every PE engagement personally. His deal-side and operating experience spans multi-billion-dollar funds and their portfolio companies in financial services, healthcare and life sciences, and industrial technology, including the $900M Ipower/Endurance acquisition by Accel/KKR that became a $3.5B public company.
The regulatory depth comes from the other side of the table: building the FDIC’s first innovation division, and current work as a non-resident Senior Technical Expert at CSIS. In regulated portfolio companies, that is usually the part of the AI thesis nobody else on the deal team can price.
Case study · pre-bid through the first 100 days
A founder-built platform, a sponsor’s AI thesis, and a modernization plan that fit inside the base case
Investment-committee read-out in under a week. Two categories of material risk found and sequenced out in year one. Modernization and agentic AI funded inside the sponsor’s existing model, with no incremental capital ask.
Read the case study
When we’re the wrong call
If the fund needs fifty engineers inside a portfolio company next quarter, hire an implementation firm. If the question is purely commercial (market sizing, customer concentration, revenue durability), use a commercial-diligence partner. If the deal is too small for senior technical diligence to pay for itself, we will say so. Distressed situations that need interim leadership at scale are also a poor fit.
Frequently asked
- Who does Virtova work with in private equity?
- Middle-market and upper-middle-market private-equity sponsors and their operating partners, family offices and strategic investors with material AI exposure, and the portfolio companies themselves. Sectors of consistent strength are U.S. financial services, healthcare and life sciences, federal contractors and adjacent industrial technology, and AI-native companies.
- Does Virtova replace our financial or commercial diligence provider?
- No. Virtova covers the technology, AI, cybersecurity, and regulatory threads. Quality of earnings, financial diligence, and commercial diligence stay with the providers the sponsor already uses, and Virtova coordinates with them so findings land in one place for the deal team.
- Does Virtova implement the technology or AI program?
- Virtova is the consulting side and does not staff implementation programs. Implementation stays with the portfolio company’s own team or the partner the sponsor selects. Virtova LLC and Frontier Foundry share ownership, and that relationship is disclosed in every engagement; no Virtova recommendation is contingent on engaging Frontier Foundry.
- Who runs the engagement, and how do you handle parallel deals?
- Sultan Meghji, personally: former inaugural Chief Innovation Officer of the U.S. FDIC and CEO and Founder of Frontier Foundry. Named specialist support is brought in only where the depth warrants it, and always disclosed in writing. If timing on a deal would compromise the senior-led model, we will say so on the first call.
- How are PE engagements priced?
- Fixed fee for scoped work such as the AI Thesis Check and Technology & AI Diligence; monthly retainer for post-close oversight, value-creation oversight, and portfolio-level work. Virtova does not publish rate cards. Fees are quoted after a discovery call and a written scope.
Bring a deal
Most engagements start with a 30-minute call.
Bring the deal context (sponsor, target, sector, deal size, indicative timeline) or a value-creation plan with an AI line in it, and we will tell you what scope fits. Confidential by default; NDAs available on request.
Book a discovery call →