micro1 is the small-cap that grew fastest in this vertical and the only one that has articulated a credible route out of the labour-arbitrage margin trap.
CEO Ali Ansari raised a $3.3M pre-seed in August 2023 and a $35M Series A at $500M led by 01 Advisors in September 2025, with Adam Bain and Joshua Browder joining the board (Sacra; TechCrunch). Revenue went from $100M ARR in December 2025 (TechCrunch) to a $500M gross run rate by August 2026 — 5x in eight months (Dataconomy; Sacra).
The December 2025 figure is reported as "$100M ARR" with no basis stated; the August 2026 figure is explicitly a $500M gross run rate. If the ARR figure was net, the growth is not 5x. No source resolves it, and the atlas carries the 5x because both sources do — not because the bases have been checked. See GMV is not revenue.
The number that matters, and the number that does not add up
micro1 claims 80–90% gross margin on "off-the-shelf" datasets resold to multiple clients (Dataconomy).
That is the single most commercially interesting claim in the vertical. Every other business here sells an hour once at a 27–40% margin. A dataset built once and licensed repeatedly has software economics, and it is the same structural escape that Mercor is buying its way toward with RL environments and that Mechanize is selling directly. What is missing is the split: nobody has disclosed what share of micro1's $500M comes from off-the-shelf datasets versus bespoke expert hours, and the 80–90% figure means very little without it.
The net-revenue reporting is internally inconsistent in its own source. The article states that micro1 retains 60–70% of gross — which on $500M would be $300–350M — and then gives net run rate as $150–200M. Those cannot both be true. The $150–200M net on $500M gross implies a 30–40% take, which matches every other take rate in the sector, and that is the reading to trust. The 60–70% retention claim should be discarded. Independently tagged [WEAK] on this point in the research notes and flagged as arithmetically inconsistent in a second compilation.
The reason this matters beyond micro1: a "$500M run rate" headline is 2.5–3.3x the number that actually accrues to the company. See GMV is not revenue and What a rake can actually be.
Supply and demand
micro1 accepts roughly the top 1% of applicants — PhDs and senior engineers (Sacra). Named customers are OpenAI and Anthropic, with a push into the Fortune 1000. That push is the strategically interesting part: enterprise buyers are more fragmented than labs, which is the only structural cure for the One customer is a binary event problem that defines this vertical. It is also, on current evidence, a small share of the book.
Ansari states micro1 does not sell to Chinese model makers (Dataconomy) — a deliberate contrast with the reporting around Surge AI and Mercor, and a hedge against an export-control regime for training data that does not exist yet but has been publicly argued for by Alexandr Wang.
Valuation
The $500M mark from September 2025 is now stale to the point of being misleading: at a $500M gross run rate it implies roughly 1x gross, or 2.5–3.3x net — by a wide margin the cheapest headline in the private cohort, and only because nobody has re-priced it. A further round at a materially higher valuation was reported to be in progress in August 2026.
Terms of the 2026 round could not be established — no size, lead or post-money is on the record.
The read
micro1 is the clearest test in the atlas of whether the dataset-resale model is real. If the 80–90% margin holds across a growing share of revenue, this is the one company in the vertical that could eventually justify a software multiple. If it stays a rounding error against bespoke expert hours, micro1 is a smaller Mercor at the same 30–40% take, and What the public market pays for labour applies to it identically.