Clockwork
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About
Clockwork provides a software-defined AI fabric designed to solve the communication bottlenecks inherent in large-scale GPU clusters. While many performance discussions focus on individual GPU speed, Clockwork addresses the reality that AI performance at scale is often limited by how efficiently thousands of GPUs communicate with one another. The platform, known as FleetIQ, integrates observability, fault tolerance, and performance optimization into a single software layer to ensure that AI training and inference jobs run without stalling or wasting expensive compute cycles. By managing the synchronization of workloads across complex infrastructures, Clockwork helps organizations turn their GPU clusters from cost centers into high-efficiency competitive advantages. The platform operates through three primary pillars that address the lifecycle of an AI job. First, AI Observability allows operators to identify slow or failing jobs and correlate them with specific infrastructure issues in minutes rather than hours. Second, AI Fault Tolerance—highlighted by the TorchPass feature—uses live GPU migration to keep jobs running even when hardware or network links fail, effectively ending the need for costly checkpoint restarts. Third, AI Performance Optimization dynamically manages traffic flow to eliminate congestion and contention, ensuring deterministic performance across the fabric. These features work together to steer traffic and route around faults in real-time, preventing the "link flaps" that commonly crash critical AI training sessions. Clockwork is specifically built for AI builders, neoclouds, and enterprise GPU cloud operators who manage massive infrastructures. It is particularly valuable for teams running large-scale model training where a single component failure can cause a multi-million dollar waste of time and resources. The software is agnostic to hardware, meaning it supports NVIDIA and AMD GPUs, as well as various network protocols like InfiniBand, RoCE, and standard Ethernet. This flexibility makes it a versatile solution for both on-premises data centers and hyperscale cloud environments looking to optimize their existing hardware investments. What sets Clockwork apart is its focus on the communication bottleneck rather than just raw compute power. By improving cluster utilization by 1.1x to 1.5x and reducing disruptive failures by over 90%, it provides a significant efficiency boost to AI factories. Unlike hardware-locked solutions, Clockwork’s 100% software-driven approach allows for rapid deployment across multi-vendor environments, providing "unflappable" fabrics that maintain stateful flows even during physical network disruptions. The system's ability to provide cross-stack visibility and dynamic traffic pacing ensures that compute resources are never left idle due to preventable network congestion.
Pros & Cons
Improves GPU cluster utilization and job completion times by 1.1x to 1.5x.
Reduces disruptive failures in GPU clusters by over 90% through stateful fault tolerance.
Compatible with multi-vendor hardware including NVIDIA, AMD, InfiniBand, RoCE, and Ethernet.
Prevents costly checkpoint restarts by using live GPU migration during hardware failures.
Offers deep observability to correlate failing jobs with specific infrastructure issues quickly.
Pricing is not publicly listed and requires a custom consultation.
Requires a high level of technical expertise to implement within enterprise environments.
The website does not offer a self-service trial or immediate software download.
Use Cases
GPU Cloud Operators can use FleetIQ to maximize cluster utilization and offer more reliable services to their end users.
AI Training Engineers can implement TorchPass to prevent job crashes and avoid wasting hours of compute time on checkpoint rollbacks.
Network Architects at large enterprises can gain cross-stack visibility to identify and resolve latency spikes in minutes instead of hours.
Infrastructure Leads at Neoclouds can manage multi-vendor environments across both NVIDIA and AMD hardware using a single software fabric.
Platform
Features
• ai performance optimization
• ai observability
• cross-stack visibility
• ai fault tolerance
• multi-vendor fabric support
• traffic flow pacing
• torchpass technology
• live gpu migration
FAQs
What is TorchPass and how does it help with GPU waste?
TorchPass is a fault tolerance feature that uses live GPU migration to keep AI training jobs running during failures. This prevents the need for costly restarts and rollbacks to previous checkpoints, which can save hours of compute time and millions in infrastructure costs.
Does Clockwork require specific networking hardware to function?
No, Clockwork's software-driven AI fabric is designed to run on any network, including standard Ethernet, RoCE, or InfiniBand. It is hardware-agnostic and supports various storage types like NVMe or object storage.
How much can FleetIQ improve GPU cluster efficiency?
Clockwork FleetIQ typically improves GPU cluster utilization and job completion times by a factor of 1.1x to 1.5x. It also reduces disruptive failures by more than 90% by dynamically routing around faults.
Which GPU manufacturers are supported by the platform?
The platform is vendor-agnostic and fully supports both NVIDIA and AMD GPUs. It can be deployed across multi-vendor environments in both cloud and on-premises configurations.
Pricing Plans
Enterprise
Unknown Price• AI Observability
• AI Fault Tolerance
• AI Performance Optimization
• TorchPass Workload Resilience
• Live GPU Migration
• Multi-vendor Support (NVIDIA/AMD)
• Cross-stack Visibility
• Free Consultation Available
Job Opportunities
Contract Technical Recruiter
Maximize GPU cluster utilization and ensure AI workload resilience with software-driven fabric that eliminates communication bottlenecks and prevents job crashes.
Benefits:
Work with a highly technical and collaborative team
Experience recruiting for cutting-edge systems
Build high-performing teams
Flexible contract role
Experience Requirements:
Proven experience as a technical recruiter
Experience hiring for early-stage startups
Strong understanding of technical roles
Experience with ATS systems
Strong understanding of programming languages
Other Requirements:
Excellent communication, negotiation, and relationship-building skills
Ability to work independently and efficiently
Responsibilities:
Partner with engineering managers to understand hiring needs
Source, screen, and engage technical talent
Manage the full recruiting lifecycle
Maintain and update candidate pipelines and tracking in ATS
Provide market insights and recommendations
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Director, Technical Partnerships
Maximize GPU cluster utilization and ensure AI workload resilience with software-driven fabric that eliminates communication bottlenecks and prevents job crashes.
Benefits:
Challenging projects
Friendly and inclusive workplace culture
Competitive compensation
Great benefits package
Catered lunch
Experience Requirements:
5+ years in partnerships, business development, solutions engineering, or technical product management
Track record driving revenue through hyperscaler partnerships (AWS, GCP, Azure)
Deep understanding of infrastructure sales motions
Experience building and scaling programs within large OEM ecosystems
Proven ability to convert technical capabilities into partner-led revenue outcomes
Other Requirements:
Executive presence with strong negotiation skills
Comfort operating in fast-paced, metrics-driven environments
Strategic thinking combined with hands-on execution
Background in AI infrastructure (Nice to Have)
Responsibilities:
Design and execute a partnerships roadmap aligned to revenue targets
Own revenue goals tied to partner-sourced and partner-influenced opportunities
Build scalable partner programs with clear KPIs
Establish and nurture C-level relationships within AWS, GCP, Azure, and OEMs
Develop sophisticated co-sell motions
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Enterprise Account Executive - East Coast
Maximize GPU cluster utilization and ensure AI workload resilience with software-driven fabric that eliminates communication bottlenecks and prevents job crashes.
Benefits:
Challenging, high-impact projects
Collaborative, inclusive, and founder-led culture
Competitive compensation and equity
Comprehensive benefits package
Experience Requirements:
Experience selling complex infrastructure or platform technologies
Track record of meeting or exceeding quota
Strong understanding of modern cloud-native and distributed architectures
Familiarity with AI/ML infrastructure
Experience selling to engineering-led organizations
Other Requirements:
Ability to articulate complex technical value
Comfortable in early-stage startup environment
Passion for building something foundational
Responsibilities:
Own and manage the full enterprise sales cycle across East Coast accounts
Build and execute strategic account plans
Engage deeply with technical buyers and senior business stakeholders
Lead complex sales processes
Partner closely with Sales Engineering, Product, Marketing, and Founders
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