- Clockwork.io has raised $31 million in new funding, taking its total capital raised to $73 million, as AI infrastructure providers look to reduce costly GPU downtime.
- LinkedIn says Clockwork.io prevents tens of thousands of GPU-hours of downtime every month, while Together AI and WhiteFiber are expanding their use of its resilience software.
- The company has launched TorchSnap, a new checkpointing technology designed to protect distributed AI workloads without code changes and accelerate reinforcement learning.
Clockwork.io has raised $31 million in new funding as the rapid expansion of AI infrastructure exposes an expensive weakness: thousands of GPUs can sit idle when a single component fails.
The round was co-led by Premji Invest, Wing Ventures and Seligman Ventures, with participation from existing investors NEA and e& Capital. The financing brings Clockwork.io’s total funding to $73 million and will support the rollout of its fault-tolerance platform across AI training, inference and reinforcement learning.
The company is targeting a problem that becomes more costly as AI models and clusters grow. Meta previously reported unexpected interruptions roughly every three hours during a 54-day Llama 3 training run involving 16,384 GPUs.
Meet the team behind Clockwork
Clockwork.io was founded in 2018 from Stanford research by Balaji Prabhakar, Yilong Geng and Deepak Merugu, with Mendel Rosenblum, the VMware co-founder, serving as chief scientist. Prabhakar is a Stanford professor whose research focuses on computer networks and data-centre systems, while Geng’s Stanford research produced the Huygens clock-synchronisation technology that became foundational to Clockwork’s platform. Merugu previously co-founded Urban Engines, which was acquired by Google.
The company is now led by Suresh Vasudevan, who joined as CEO after leading Sysdig and Nimble Storage. At Nimble, he took the company through an IPO and its eventual acquisition by HPE. He also held senior leadership roles at NetApp.
From GPU failures to live recovery
Clockwork’s argument is that conventional checkpoint-and-restart systems are increasingly inefficient for large distributed AI workloads.
A failed GPU, network link, NIC or server can force an entire training job to restart from its last checkpoint, potentially losing hours of completed work and leaving healthy GPUs idle.
Clockwork’s software sits between infrastructure and workloads to keep jobs running through those failures.
LinkPass reroutes network traffic around failed links, while TorchPass moves workloads from failing GPUs to healthy ones without requiring a complete restart. TorchSnap adds another layer by capturing the state of distributed AI jobs across multiple nodes.
For training, its platform snapshots can preserve a running job without requiring changes to the training code. Its faster application checkpoints can also help reinforcement-learning systems move updated model weights to inference replicas more quickly.
“Failures are inevitable at AI scale. Losing hours of useful work to them should not be,” said Suresh Vasudevan, CEO of Clockwork.io. “Fault tolerance is a goodput multiplier: it keeps GPUs doing useful work instead of waiting for recovery or repeating work already done. We built our software alongside enterprises and cloud providers operating some of the largest GPU fleets, so it handles the failures they actually see. That protection belongs in the infrastructure enterprises and cloud providers rely on every day.”
LinkedIn and AI clouds join the push
LinkedIn has deployed Clockwork’s LinkPass across its AI infrastructure and says it prevents tens of thousands of GPU-hours of downtime each month.
Together AI is bringing TorchPass to its GPU clusters, while WhiteFiber is expanding Clockwork across its global GPU-as-a-service infrastructure.
The AI infrastructure race
The opportunity extends beyond fault tolerance. Gartner forecasts global AI spending will reach $2.7 trillion in 2026, up 49.5% year over year, with AI infrastructure representing the largest spending category.
That infrastructure boom has created a wave of heavily funded players. Together AI raised $800 million at an $8.3 billion valuation in its latest round, while Crusoe recently raised more than $3 billion at a $30 billion valuation. Nscale has also raised $3.36 billion in pre-IPO financing.
Clockwork is attacking a different layer of the same infrastructure stack: ensuring that the enormous amount of compute being deployed actually gets used.
With AI clusters becoming larger, more expensive and harder to keep synchronised, Clockwork’s bet is that resilience will become as important as raw GPU performance.
“Clockwork treats failure as the normal state: TorchPassmigrates training off a failing GPU live; TorchSnap snapshots an entire running job with no code changes. It’s already saving tens of thousands of GPU-hours a month. We first backed Clockwork in 2021 and are thrilled to keep supporting them as they define the performance layer of the AI cluster,” said Greg Papadopoulos, Venture Partner, NEA.
