Labelbox, which offers data annotation and labeling software, raises a $110M Series D led by SoftBank Vision Fund 2; CEO says Labelbox is “basically a unicorn”
Context & Ripple Effects
Labelbox has been raising on a steady cadence: a $10M Series A in 2019, a $25M Series B led by a16z in 2020 to grow its AI-training data-labeling platform, and a $40M Series C led by B Capital Group in 2021 that brought its total to $79M. The $110M Series D more than doubles that war chest in a single round.
The new lead investor matters as much as the amount: SoftBank Vision Fund 2 was deploying at an aggressive pace through this window — $22.8B across 65 deals in Q3 2021 and $9.9B in Q1 2022 — and Labelbox becomes one of its data-infrastructure bets. The CEO's 'basically a unicorn' framing signals the company is pricing itself at the category's new ceiling.
First-order effects
- Labelbox's total raised jumps from $79M to roughly $189M, giving it capital to scale the data-labeling platform while competitors like CloudFactory — which had raised $65M for a $78M total back in 2019 — work with older, smaller war chests.
Second-order effects
- The round validates data labeling as a fundable category, drawing later entrants: Cleanlab raised a $25M Series A at a $100M valuation in 2023 selling tools for more accurate training data, showing the niche kept attracting capital even after Labelbox's scale-up.
Third-order effects
- Training-data tooling is consolidating into a distinct, heavily capitalized layer of the AI stack, with mega-funds like Vision Fund 2 — investing at roughly twice the pace of its predecessor fund — effectively deciding which annotation platforms get the scale to survive.
The trend: Data labeling and training-data infrastructure is becoming a capitalized category of the AI stack, with mega-fund investors like SoftBank Vision Fund 2 concentrating capital into a few platform vendors.