Anonymized at the sponsor’s request. The sponsor, the portfolio company, its sector, and any detail that could identify either are withheld, as is standard for the sponsors Virtova works with. This account describes the process and the outcome, not the company. Specifics are available to prospective clients under a mutual NDA, with the sponsor’s consent.
Session → IC read-out
<1 wk
Incremental capital ask
$0
Risk categories, sequenced out in year 1
2
Core platform logic
Kept
The engagement at a glance
A private-equity sponsor was acquiring a founder-led services business whose operations ran on a platform the founder had built in-house.
The sponsor’s value-creation plan leaned on technology: organic expansion, add-on acquisitions, pricing optimization, and automation of manual workflows. The investment memo flagged the homegrown platform as a likely rebuild-or-replace. Virtova was engaged to size that, find what the data room didn’t show, and give the investment committee a plan it could underwrite.
Pre-bid: the question that moved the model
The question at the IC table was not whether the software was modern. It wasn’t. It was whether the platform could carry the value-creation plan, and what it would cost to make it do so. Two answers mattered for the bid: whether the system’s value was in code worth keeping or in the data and logic underneath it, and whether the modernization cost sat inside the model or on top of it.
Diligence: what we found
Working from the management technology session and the IT materials in the data room, Virtova delivered the read-out to the investment committee in under a week. It covered the current state, the risks, the target architecture, and a costed plan.
What was worth keeping. The core business logic, the part of the platform that actually creates value, was well-honed, and the underlying data was in good shape. The recommendation was to preserve and re-platform that core, not rebuild it. That is why the cost estimate stayed modest.
Risk category one: key-person concentration. Critical knowledge of the platform sat with too few people, without the engineering controls and documentation that would let anyone else take it over, at the same moment ownership and leadership were changing.
Risk category two: end-of-life infrastructure. Production systems ran on out-of-support software and hardware with single points of failure, which is both an availability risk and a security exposure.
An architecture that constrained growth. The way the platform was delivered and connected, more than the age of any component, limited the expansion, add-on integration, and AI the value-creation plan depended on. It shaped the target architecture.
Confirmatory items. The read-out named what would move the estimate: data and schema quality, the scope of systems in play, security depth on personal-data handling, and confirmation that the company cleanly owned its code.
The plan: preserve the core, modernize the scaffolding
Year one, the “Version 1” build. Sequenced by quarter:
- De-risk and control. Engineering controls, code ownership at close, structured knowledge transfer, and a security baseline.
- Re-platform. Move off end-of-life infrastructure, with the core logic ported intact.
- Integrate and automate. Replace manual hand-offs between systems with integrations, and automate the highest-volume manual workflows, including first AI use cases.
- Modernize and unlock scale. Modern, browser- and mobile-based delivery, an internal API layer, and removal of the constraints that would have slowed expansion and add-on integration.
Year two onward, operate and extend. An ongoing engineering partner plus a lean internal technology owner, so platform knowledge lives in a team rather than one replacement hire. Agentic AI rolled out across the operating workflows, plus an integration playbook for add-on acquisitions.
Key-person mitigation was the build itself. Re-platforming alongside the people who built the system is the knowledge transfer. The plan paired it with day-one code ownership and transition arrangements through Version 1.
Funding. The one-time build fit inside the year-one capex already in the sponsor’s model, and the ongoing run-rate fit inside the existing technology SG&A line. No incremental capital ask.
Close and the first 100 days
The acquisition closed, and the first 100 days ran against the plan, starting with the de-risk-and-control work. The same team that ran the diligence carried the findings into the 100-day plan, so nothing was lost at close.
Why it mattered for the deal
The sponsor walked into the investment committee with the technology question answered: what the company owned, what it would cost to modernize, which risks were real and how they would be retired, and how the automation and AI levers in the value-creation plan would actually get built. An open item in the memo became a costed, sequenced plan that fit the model.
Disclosure. Virtova was the consulting side of this engagement, and Frontier Foundry was the implementation side of the technology build. Sultan Meghji is the founder of Virtova LLC and the CEO and Founder of Frontier Foundry; the two firms share ownership. The relationship is also documented at /editorial/.
Engagement model
AI Thesis Check and Technology & AI Diligence before signing, followed by the 100-Day Technology & AI Plan. See the Virtova private-equity practice for how the offers fit together.