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Founders Mentioned

Hugo Santos

Namespace Labs

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Hugo Santos

Namespace Labs

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March 25, 2026
Ai AgentsDeveloper ToolsDevops AutomationAi InfrastructureStartup Funding

Namespace Raises $23M to Build 'Compute Layer for Code' at Agent Speed

NEA leads round for ex-Google founders building CI/CD infrastructure that's 2x-10x faster. Timing aligns with surge in AI coding agents and GitHub Actions pricing shifts.

Namespace Raises $23M to Build 'Compute Layer for Code' at Agent Speed

Hugo Santos spent nearly a decade inside Google's infrastructure machinery, building the kind of plumbing most developers never see—the systems that keep Search, Photos, and Assistant humming beneath the surface. Now he's trying to bring that same obsessive focus on speed to the rest of the software industry, one CI/CD pipeline at a time.

Namespace Labs, the company Santos founded, announced $23 million in combined seed and Series A funding on March 23, 2026. NEA led the raise, joined by Susa Ventures and burst.vc. The pitch is straightforward, if ambitious: build what Namespace calls "the compute layer for code"—infrastructure that runs continuous integration and deployment pipelines anywhere from twice to ten times faster than standard hosted runners.

The timing, perhaps more than the founders expected, couldn't be sharper. GitHub Actions had just unveiled sweeping pricing changes: cuts to hosted runner costs effective January 1, 2026, and a new platform fee for self-hosted runners that was supposed to land March 1 (GitHub later postponed it for reconsideration). Those shifts sent ripples through engineering organizations already wrestling with CI economics, and suddenly alternatives that promise speed and cost efficiency started looking more attractive.

Hardware, Not Just Software

Unlike pure software plays, Namespace operates its own hardware across multiple data centers. The company supports Linux, macOS—including Apple Silicon M4 Pro at scale, a configuration that's still relatively rare in hosted environments—and Windows. Built-in caching, observability tooling, and what the company describes as "incremental runs" that skip redundant work are core to the platform.

Namespace has attracted customers including fal.ai, LiveKit, Framer, Vanta, Verkada, and Zed. Warp, the terminal startup leaning hard into AI-assisted coding, published an engineering deep-dive explaining how it used Namespace to architect "secure cloud sandboxes for AI dev," calling out experimental API features like sidecar volumes. A Namespace comment on Reddit's r/programming claimed the company powers Buildkite's hosted agents, though Buildkite's public documentation doesn't name vendors—one of those data points that's either strategic discretion or just an NDA at work.

Santos's background runs through Google's Boq platform, the microservices backbone for some of the company's largest products. Before Google, he co-founded Blaast, an edge compute venture that Facebook acquired. The Namespace team draws heavily from that Google infrastructure lineage. It's the kind of pedigree that opens doors in developer tooling, where "we've done this at scale before" carries real weight.

The AI Angle

Digital illustration for article section "The AI Angle" in "Namespace Raises $23M to Build 'Compute Layer for Code' at Agent Speed" - A conceptual illustration of an isolated cloud environment representing an AI "Devbox," featuring a ...

Three weeks before the funding announcement, on March 3, 2026, Namespace publicly released Devboxes—isolated cloud environments built explicitly for what the company calls "remote coding agents." It's a clear signal about where Santos thinks the market is heading: not just faster builds for humans, but infrastructure ready for AI assistants that write, test, and deploy code autonomously.

Whether that bet pays off is an open question. AI coding tools have exploded in adoption, but the workflow and infrastructure requirements are still being figured out in real time. Namespace is wagering that purpose-built compute will matter as these agents move from experimental to production-grade.

The company says it will use the new capital to boost performance, expand platform capabilities, and lean further into agent-oriented workflows across all three operating systems. Namespace already holds SOC 2 Type II attestation—table stakes for enterprise sales—and claims hundreds of teams as customers, though it hasn't disclosed user counts or revenue. That's standard for early-stage infrastructure companies, but it also means traction is still somewhat opaque from the outside.

Competing in a Crowded Space

Digital illustration for article section "Competing in a Crowded Space" in "Namespace Raises $23M to Build 'Compute Layer for Code' at Agent Speed" - A clean, minimalist conceptual illustration representing fierce competition and rapid build speed in...

The CI/CD market is fragmented and fiercely competitive. GitHub Actions, CircleCI, Buildkite, and a handful of others all compete for developer mindshare, while surveys from the Cloud Native Computing Foundation and Continuous Delivery Foundation consistently highlight build speed and test environment friction as top pain points. Namespace's hardware-first model is differentiated, but switching costs in this category—while not insurmountable—are real. Teams invest heavily in pipeline configurations, custom tooling, and institutional knowledge around their CI systems.

What Namespace has going for it: a founding team with credibility in infrastructure circles, a product that appears to deliver on its speed claims (at least according to early adopters), and a market moment when pricing volatility has made engineers willing to reconsider their defaults. What's still unproven is whether that's enough to build a durable, defensible business in a space where the giants—GitHub especially—can always decide to compete more aggressively.

For now, Santos is betting that the combination of raw performance and purpose-built tooling for the next generation of AI-assisted development will carve out space. It's worked before for infrastructure startups with deep technical chops. Whether it works this time will come down to execution, customer retention, and whether the AI coding wave turns out to be as transformative as the hype suggests.

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