Optimize Network Performance

Get the absolute maximum return on your AI hardware investments by ensuring your network never throttles your compute capabilities. Hedgehog delivers a seamless, out-of-the-box deployment experience for your AI cloud infrastructure—no network engineering degree required. You don't need to parse the differences between a collapsed core, mesh, clos, or rails topology. Just define your use case, and Hedgehog automatically provisions the exact fabric that fits, delivering hyperscale performance without the hyperscale engineering overhead.

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Designed for AI Workloads

Tuned specifically for the extreme scale of AI, the fabric automatically optimizes complex traffic flows under the hood and eliminates configuration drift to maintain perfect state optimization. This precise traffic management slashes training time-to-completion and drives up inference tokens per second. Combined with open observability and proven network recipes, Hedgehog ensures your cluster operates at peak capacity, guaranteeing your GPUs are always fed and never idle.

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Real-Time Edge Intelligence Fabric

Low-Latency AI Networks at the Edge

Edge AI requires specialized network architecture that minimizes latency and maximizes reliability. Hedgehog Edge Intelligence Fabric provides the networking foundation for real-time decision making directly at the point of data collection.

Network advantages for edge AI workloads:

  • Ultra-low latency connectivity eliminates the need for cloud round-trips
  • Resilient local clusters ensure continuous operation even during connectivity interruptions
  • Support for commodity hardware provides cost-effective infrastructure without vendor lock-in
  • Zero-touch lifecycle management (ZTLM) automates installation, configuration, and ongoing operations

Perfect for networking smart camera arrays in manufacturing environments, 5G-connected drone fleets requiring real-time coordination, mobile command centers and other edge solutions where real-time intelligence needs requires consistent local networking performance.

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Retrieval-Augmented Generation (RAG) Fabric

Balanced Networks for Hybrid Workloads

RAG architectures demand consistent performance across complex network paths. Hedgehog RAG Fabric delivers a balanced Clos network topology specifically tuned for the unique traffic patterns between databases and language model servers.

Network advantages for RAG workloads:

  • Optimized traffic distribution for high-volume database queries
  • Balanced east-west bandwidth ensures consistent cross-component communication
  • Simplified network expansion as vector database requirements grow
  • Low-latency routing across the network fabric

Perfect for network infrastructure supporting enterprise search applications, customer support systems with complex query patterns, or code assistance platforms requiring rapid data retrieval and processing.

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AI Fine-Tuning Fabric

Networks That Handle Gradient Bursts

Fine-tuning creates unpredictable network traffic patterns. Hedgehog Fine-Tuning Fabric automatically configures lossless QoS policies via EVPN, ensuring critical traffic flows remain unaffected by microburst congestion.

Network advantages for fine-tuning workloads:

  • Prioritized gradient synchronization prevents packet loss during traffic spikes
  • Faster training convergence through optimized network parameters
  • Automated QoS configuration with pre-tuned policies for AI workloads
  • Rapid network provisioning through streamlined API calls

Perfect for research labs adapting foundation models to specialized domains, financial institutions running nightly domain-specific training, or healthcare organizations fine-tuning diagnostic models where consistent network performance directly impacts model convergence time and quality.

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AI Training Fabric

Purpose-Built Networking for AI Model Training

High-performance AI training demands specialized network architecture. Hedgehog Training Fabric delivers a dual-path network design that intelligently manages compute and storage traffic—all through our intuitive cloud-native API.

Network advantages for training workloads:

  • Optimized training throughput with specialized fabric configuration for low-latency network communication
  • Segregated traffic paths prevent storage operations from impacting training traffic
  • Flexible network scaling with support for multiple topologies as your cluster grows
  • Zero-touch BGP-EVPN configuration with automated installation and provisioning

From pharmaceutical QA labs running distributed training to AI research centers requiring multi-rack infrastructure, Hedgehog Training Fabric ensures your network architecture never becomes the bottleneck in your AI pipeline.

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High-Performance Data Center Fabric

Enterprise-Grade Networking Made Simple

Modern data centers run diverse workloads with varying network requirements. Hedgehog Data Center Fabric delivers enterprise-grade traffic isolation and consistent performance through a single, intuitive cloud-native API.

Network advantages for mixed workloads:

  • Automated tenant isolation with VPC-based network segmentation
  • Performance-based traffic management ensures predictable application response
  • Simplified capacity expansion with spine-leaf architecture
  • Advanced traffic classification for diverse application requirements

Perfect for connecting infrastructure in multi-tenant environments, enterprise data centers with varied application demands, or computing clusters requiring precise resource allocation and isolation.

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