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DigitalOcean agrees to acquire NY-based Paperspace, which offers cloud computing for AI models, for $111M in cash; Paperspace had raised $35M from YC and others

Kyle Wiggers / TechCrunch :

TechCrunch Kyle Wiggers

Context & Ripple Effects

Paperspace has been on the market's radar since its $13M Series A led by Battery Ventures in 2018, pitched as an 'AI-fueled application development platform.' Five years and roughly $35M of total funding later, it exits for $111M in cash — a modest multiple that reflects how capital-intensive AI compute became relative to what a startup of its size could self-fund.

For DigitalOcean, this is the second straight cash acquisition aimed at moving up the stack: last year it bought managed-hosting firm Cloudways for $350M (around half of whose clients already used DigitalOcean), extending an infrastructure base it expanded via debt back in its $130M borrowing round in 2016. Paperspace extends that same playbook from web hosting into AI workloads.

First-order effects

  • DigitalOcean gains a cloud offering purpose-built for running AI models overnight, buying capability instead of spending years on organic GPU infrastructure buildout; Paperspace's backers, including Y Combinator, exit a $35M investment for $111M in cash.
  • Paperspace stops being an independent vendor — its customers now sit inside a much larger cloud's portfolio alongside DigitalOcean's existing developer base.

Second-order effects

  • Independent AI-cloud rivals such as Lightning AI, which raised $50M to let customers fine-tune and run models across their preferred clouds (bringing its total funding to $103M), now face a competitor that bundles AI compute with cheap general-purpose hosting.
  • The sub-$150M price point sets a reference for other small AI-compute startups weighing sale versus another funding round — and signals to remaining independents that acquirers will pay cash, not stock, for this layer.

Third-order effects

  • If the pattern holds — Cloudways then Paperspace — mid-tier clouds are consolidating the managed-AI layer through M&A, concentrating developer-facing AI compute among fewer providers while hyperscalers fight at the raw-capacity level.
  • Exit multiples near 3x lifetime funding suggest AI compute startups that don't reach scale face acquisition rather than independent growth, shaping how founders in this category structure fundraising.

The trend: Mid-tier cloud providers are buying their way into AI compute through targeted acquisitions rather than competing with hyperscalers on organic infrastructure spend.