For private equity
Why we focus on private equity.
We've lived the portfolio-company operating model. We think at the portfolio level and act at the operating-company level — and we tailor each engagement to a whole-of-company view.
That's what's different: not generic AI advice, but operators who know value is created one portfolio company at a time — and compounded across the portfolio.
The 2026 reality
Returns have to come from operations now.
Multiple expansion is gone. Hold periods are stretching and DPI is under pressure. The bar for value creation has roughly doubled — operational EBITDA growth, not financial engineering, now carries the return. AI is the mechanism, and standing still is a decision with a cost.
For the GP
Operating alpha, fast.
We grow EBITDA, release working capital, and lift revenue — proven on your data in 30 days, then repeated across the portfolio — and compounded at the exit multiple.
For the LP
A fund that can operate.
AI-proven EBITDA growth inside the hold compresses payback and lifts MOIC — a documented value-creation track record that defends IRR at the LP report and supports the next fund close.
Why Helix
We own the outcome.
We build and run it, and own the result — not just the advice. That's the difference between an operating partner and an advisor.
Why PE hires us
Value before the deal, and after.
We're the operating partner that builds AI into the portfolio — and we've lived the job. We work two windows.
Before — diligence
Underwrite the AI upside.
Before you bid, we run an AI-readiness diligence — the AI equivalent of technical diligence: is the data accessible and AI-usable, what cost can come out, and what value AI can add. You get a sized value-creation case as Architect, a buildability read as General Contractor, and an adoption read as Interior Designer — a sharper thesis and a more confident bid, backed by a proof of value, not a hunch.
After — the hold
Build the value, then repeat it.
We build and run the AI that grows EBITDA, lifts revenue, and frees working capital — proven in 30 days, then lifted-and-shifted across the portfolio. Operating alpha you can show at the next mark, and a cleaner exit story.
Think at the portfolio level. Act at the operating-company level.
Why this matters in PE
Operating gains compound at the multiple.
$10M of EBITDA, at a 10× exit multiple, is $100M of enterprise value — and the proven model lifts-and-shifts across the portfolio, each deployment 30–60% less expensive than the last. (Illustrative.)
And the multiple itself can move. An AI-native operating capability your competitors don't have is a valuation premium — alpha the comp set can't price in. It isn't just peer financial arithmetic.
Where we specialize
Built for the funds that own the value stack.
Private equity firms live by one number — the value created within the hold period: revenue, EBITDA, working capital, and the exit multiple it earns. Most AI efforts stall in the same place — the wrong projects, unproven ROI, and pilots that never scale. We close that gap — we find where AI moves the value stack, prove it in weeks, and lift-and-shift the wins across the portfolio.
We concentrate where operational complexity meets real data — distribution, logistics, financial services, and broadband — and go wide across the portfolio once the model is proven.
Problems we solve
A few examples — not exclusive.
If one of these is keeping you up at night, that's where we start.
Start with a Proof of Value