C

Clockwork Systems

Advanced clock synchronization for distributed systems

Overview

Clockwork Systems provides clock synchronization technology for mission-critical distributed systems, ensuring precise timing across operations. Its solutions run in both cloud and on-premises environments and are delivered through software licensing, subscriptions, and professional services. The company differentiates itself with deep timing expertise and end-to-end timing across networks, framed by tools like Latency Sensei for cloud latency monitoring. Its goal is to help customers achieve reliable, accurate synchronization to boost performance and reduce timing-related issues in time-sensitive applications.

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About Clockwork Systems

Simplify's Rating
Why Clockwork Systems is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsEnterprise SoftwareFinancial ServicesGaming

Company Size

51-200

Company Stage

Late Stage VC

Total Funding

$72.6M

Headquarters

Palo Alto, California

Founded

2018

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Simplify's Take

What believers are saying

  • Clockwork launched FleetIQ on 2025-09-10, expanding from timing into AI infrastructure optimization.
  • The company says FleetIQ reduces crashes, restarts, and idle GPU waste immediately.
  • Forge Global listed a $357M Series A-1 valuation on 2025-09-10, signaling investor support.

What critics are saying

  • Dynatrace, Datadog, and SolarWinds Observability attack adjacent monitoring budgets aggressively.
  • Latka shows only 41 employees and $4.5M revenue, limiting enterprise sales capacity.
  • FleetIQ targets AI infrastructure already dominated by NVIDIA networking partnerships and hyperscaler control.

What makes Clockwork Systems unique

  • FleetIQ unifies nanosecond visibility, traffic control, and job-aware resilience across fabrics.
  • ClockSync aligns hosts, NICs, and switches to sub-microsecond timelines for correlated telemetry.
  • Runs across cloud and on-prem, supporting NVIDIA, AMD, InfiniBand, RoCE, and Ethernet.

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Funding

Total Funding

$72.6M

Above

Industry Average

Funded Over

3 Rounds

Late VC funding comparison data is currently unavailable. We're working to provide this information soon!
Late VC Funding Comparison Coming Soon

Benefits

  • Competitive Salary

Growth & Insights and Company News

Headcount

6 month growth

-11%

1 year growth

-45%

2 year growth

-38%
Associated Press
Mar 11th, 2026
Clockwork.io launches TorchPass to eliminate GPU failure waste in AI training, saving $6M per 2,048-GPU cluster

Clockwork.io has launched TorchPass Workload Fault Tolerance, a software solution that eliminates costly GPU training failures through Live GPU Migration technology. The system allows AI training workloads to continue running through hardware failures, network disruptions and node crashes without requiring checkpoint restarts. The company claims TorchPass can save over $6 million annually in a typical 2,048-GPU deployment by reducing wasted training progress by 95%. In large clusters, it cuts lost time from approximately three hours per day to under ten minutes. Independent testing by SemiAnalysis found TorchPass delivered faster fault-tolerant performance than standard checkpoint-restart approaches and higher Model FLOPs Utilisation than leading open-source alternatives. The solution typically completes recovery in approximately three minutes whilst training continues uninterrupted. TorchPass is now available as part of Clockwork.io's FleetIQ platform.

The SaaS News
Sep 11th, 2025
Clockwork Raises $20.57 Million in Funding | The SaaS News

Clockwork Raises $20.57 Million in Funding

TechStartups
Sep 10th, 2025
Clockwork Systems Raises $20.6M for FleetIQ

Stanford spinout Clockwork has raised $20.6 million, led by NEA with participation from notable investors, to address AI's GPU inefficiency. The funding coincides with the launch of FleetIQ, a software solution aimed at enhancing GPU performance by improving communication between GPUs, clusters, and clouds. This innovation seeks to reduce crashes, shorten restarts, and increase utilization rates, making AI infrastructure more efficient and sustainable.

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