There is more EBITDA value sitting in your portfolio company that your deal model never assumed. We find it, and build the systems to capture it.
At Virage, we've consistently seen 20–30% productivity gains in knowledge-work functions when agentic systems are deployed against the right friction points — and none of that upside was in the original underwriting.
They're running the playbook they know. But the playbook was written before AI changed what's operationally possible. Upskilling and tooling them is faster and cheaper than you think.
Legacy systems aren't going away, and full migrations aren't realistic mid-hold. The opportunity is injecting intelligence into what's already there — reducing human dependency without platform risk.
Your competitors are taking the steps you're not. The operational gap is widening at an accelerating pace. That's a risk you can't afford to defer.
Your people are the fastest lever. We upskill your knowledge workers on AI tools that apply to their actual jobs, not generic training. Admin time drops, output per head goes up. Measurable within days.
We start with the audit by mapping how work actually moves through your organization. Then we automate the steps that don't need a human. No platform migrations. Less manual input, same systems, more output.
We rebuild the operational architecture from the ground up. Not optimizing existing workflows - replacing them. Agentic systems run autonomously so your people focus on what actually requires human judgment.
Adjust the inputs to your portfolio company's profile. Outputs use a 20–30% gross productivity gain range — consistent with published research on agentic AI in knowledge-work functions — converted to EBITDA at your chosen conversion rate.
Gross productivity gain of 20–30% is applied to your knowledge-worker cost base, consistent with McKinsey and BCG published research on agentic AI in knowledge-work functions. The conversion rate reflects what portion of that gain is captured as EBITDA versus reinvested in growth or absorbed operationally. These are illustrative ranges — actual results depend on operational topology, deployment scope, and timing within the hold.