About & Consulting
Divergent Compute measures the distance between what markets price and what the math allows — across the AI build-out, and inside our own operation.
The dual mandate
We cannot credibly analyze the economics of AI from the sidelines. So we run an AI-native research operation and instrument it — making the firm itself a live data point on the productivity, labor, and capital shifts it studies.
We don't just speculate on the future of the economy. We use the tools shaping it.
What we measure
How we work
Credibility is the only thing we sell, so we engineer for it. Verified figures trace to primary filings. Attributed estimates are named as such. Unverified figures are flagged or removed — never dressed up. Every thesis pillar carries an explicit falsifier, and we revise in public.
The work runs on three surfaces that feed each other: a publication that reports the divergence, research that measures it, and consulting that applies the instruments inside your operation.
Consulting
We don't just publish on the economics of AI. We deploy the same instruments inside your operation, and tell you what the math says about your build-out before the market reprices it. The published research proves the method; the engagement applies it to you.
Diagnostic
Where compute spend is, and isn't, converting to output across your workflows — measured, not estimated.
Benchmark
Your productivity yield against our adoption-frontier index — how far ahead or behind the curve you actually are.
Advisory
An independent read on the durability of an AI capital plan — the two-clocks framework, applied to your decisions.
For corporate strategy teams sizing an AI build-out, investors underwriting one, and operators who need to know whether their spend is ahead of or behind the return. Engagement enquiries opening soon — the research is open now, start there.