DigitalOcean Holdings, Inc. Q1 FY2026 earnings call

First, momentum is accelerating with Q1 revenue growth, million-dollar-plus customers and AI customer ARR growth. Second, launched the DigitalOcean AI Native Cloud, a significant product launch with five fully integrated layers. Third, invested $888 million in equity to strengthen balance sheet and secure 60 megawatts of incremental capacity. Fourth, raised near and medium-term guidance with 2026 revenue growth projection increased and 2027 revenue growth expected to be 50% or more. Also, discussed the agentic era, new product launches, and the importance of open source and integrated platform for AI native companies.

Q1 revenue was $258 million, up 22% year over year. Million-dollar-plus customers growing 179% year-over-year to 183 million in ARR. AI customer ARR grew 221% to 170 million. ARR from $100,000 customers grew 73%, while $500,000 customers ARR grew 132%. ARR from $1 million plus customers reached 183 million, growing at 179% year over year. Inference and core cloud pull-through increased to more than 80% of total AI customer ARR. First quarter adjusted EBITDA was $105 million, up 21% year over year, with an adjusted EBITDA margin of 41%. Trailing 12-month adjusted free cash flow was $171 million, or 18% of revenue.

For 2026, expect revenue growth of approximately 25% to 27% year-over-year with an exit growth rate approaching 30%. Adjusted EBITDA margins expected to be high 30s and adjusted free cash flow margins 9% to 12%. For 2027, expect revenue growth of 50% or more, with approximately 40% adjusted EBITDA margins and high teen adjusted free cash flow margins. Second quarter of 2026 expected revenue of $272 million to $274 million, 24% to 25% year-over-year growth. Second quarter adjusted EBITDA margins in the range of 37% to 38%.

Q: How relevant is the CPU renaissance for business and quantitative benefit?

A: Moving to agentic era requires more compute, new capacity is deploying full stack AI native cloud.

Q: Extent software capabilities can push revenue per megawatt higher?

A: Optimistic about driving arr per megawatt up with stickier services.

Q: How to think about B and raise cadence?

A: Richmond Data Center came online earlier, able to sell into it, pricing not seeing compression.

Q: Demand signals to watch?

A: ARR per megawatt, token efficiency.

Q: Contributions from new land vs existing conversions?

A: Healthy mix of new AI native customers and existing enterprise customers ramping up AI workloads.

Q: Sustainability of differentiation relative to neoclouds?

A: Our stack is well-integrated, open source, different from neoclouds focusing on training.

Q: Penetration of AI-driven workloads in customer cohorts?

A: Yes, expect numbers to keep going up.

Q: Customer selectivity and capex per megawatt?

A: Balancing pipeline, capex per megawatt higher with higher token capacity equipment.

Q: GPU and other pricing trends impact?

A: Have ability to adjust to market, more readily than some others.

Q: Gross margin profile of incremental capacity?

A: Operating margin better view, strong and compelling, will see small decrease with new capacity investment.

Q: Why customers enthusiastic about inference router and DeepSeq model?

A: AI natives run multiple models, open source, router important for finding right model, deep seek support due to open source embrace.

Q: How Cursor fit into guidance?

A: Fantastic customer, not predicating long-term guidance on single customer.

Q: Inning of inference and data center capacity constraint?

A: Inference in top of second inning, data center capacity still in active conversations for additional capacity.