M&A advisory for AI & ML companies
AI M&A is younger than software M&A, weirder, and moves faster. Deals span everything from sub-USD-50m acqui-hires for a research team to multi-billion-dollar strategic acquisitions where the asset is essentially a model, a dataset and twenty people. Revenue is often early, training-data provenance is often messy, and the buyer cares about completely different things than they would in a normal software deal.
The active buyer set is concentrated. Hyperscalers and platform strategics (Microsoft, Google, Meta, Nvidia, Apple, Amazon) move on talent, IP and infra alignment; the larger SaaS incumbents acquire to plug AI capability into existing distribution; PE is starting to underwrite applied-AI businesses with genuine ARR. Diligence centres on training data rights, model architecture, GPU commitments, and how gross margin behaves once inference scales - not the multiple-on-revenue conversation a SaaS deal hinges on.
We've been advising founders and investors building the AI stack from the start of the current cycle, and run sell-side processes built around how AI assets actually get valued today.
M&A goes smoother with an advisor that understands AI & ML
Frame the asset properly
An AI company can be sold as a product, a team, a dataset or a model - and the same business is worth wildly different numbers depending on which framing wins. We figure out which buyer narrative fits the asset, and position the company accordingly before any name is approached.
Hyperscaler and strategic access
We work the corporate development teams at the platform acquirers (Microsoft, Google, Meta, Nvidia, Apple, Amazon) and the SaaS strategics now buying AI capability into their stacks. We know who's actively transacting and who is just taking meetings - the difference is months of process time.
Diligence-proof the data
Training-data provenance and licensing rights are where AI deals quietly fall apart in legal diligence. We pre-empt the data audit, structure rights and reps around what acquirers can actually live with, and avoid the late renegotiation that compresses headline value by 20-40%.
Unit economics under stress
Buyers model AI gross margin at 10x current usage to test where inference cost lands. We build the same view first, so the COGS and pricing story is bulletproof when finance diligence opens up - and earn-outs aren't tied to margin levels the unit economics can't deliver.
Recent M&A deals we closed
We've closed sell-side and buy-side transactions across European, US and emerging-market tech.
Our M&A track record spans strategic exits to corporate acquirers, PE buyouts, and cross-border deals where regulatory and structuring complexity actually matters.
We provided buy-side advice to Boryszew, a Warsaw-listed diversified industrial group across automotive, metals and chemicals, on industrial software market mapping and target screening for its buy-and-build strategy.
Recent M&A advisory AI & ML track record
Selected M&A transactions and prior deal experience.
M&A advisory for all AI & ML niches
From AI software to AI infrastructure & semiconductors, we're a specialized M&A advisor to AI & ML companies.
Our M&A experience spans across all AI & ML verticals.
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We know tech inside & out.
We live and breath tech - true understanding of how startups operate is fundamental at what we do.
Recent AI & ML insights
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