We give advisors a fast, credible way to tell the difference, and the team to close the gap if it’s worth closing before the deal, not after.
The same AXIS framework, one rubric, run on a company in a live process. A read a buyer can trust, not a slide the target wrote about itself.
Whether you run it pre-close or we’re introduced to the new owner post-close, the target walks away with a real assessment, not just your due-diligence file.
When a company surfaces an opportunity bigger than a workflow, we have a fund and a team. We co-invest alongside it, not sell an add-on engagement.
Every company we look at is scored on the same four dimensions, then placed on the Autonomy Stack, Curious to Connected. That’s what makes the read comparable across a target and its peers, not just impressive in isolation.
Four questions that tell a real AI-maturity claim from a slide-deck one, before it’s in your model.
A confident AI story doesn’t close a deal. A verified one does.
Strategy firms sell advice and leave. We run a venture studio and a co-investment fund, and the same discipline that finds an edge inside a company we’re building from scratch is what we bring to whatever’s in your data room.
Shegun built and exited Therapy Brands for $1.25B before founding HVL. The read we give you comes from someone who’s actually built the thing, not audited it.
No. The assessment runs in two weeks, in parallel with the process, and the output is a document the target can hand to buyers, not a new gate to clear.
Those tools use AI to move faster through a data room. This runs the other direction: we diligence the target’s own AI claims, not your paperwork.
You and the target, by default. It becomes part of what the target can show a buyer, not a private score sheet you’re keeping on them.