A modern, scalable infrastructure designed for high-compute AI workloads. Powered by Amazon Bedrock foundation models and optimized for enterprise deployments.
Multi-layered design for maximum flexibility and performance
Native access to state-of-the-art foundation models
Direct integration with Claude, Llama, Titan, and other leading foundation models through Amazon Bedrock's unified API. Switch models without code changes.
Built-in prompt templates and optimization for infrastructure configuration. Our semantic engine uses advanced prompting techniques for accurate intent understanding.
Knowledge-augmented generation with Amazon Kendra integration. Ground agent responses in your enterprise data with real-time retrieval.
Content filtering, PII detection, and safety controls built into the inference pipeline. Customizable policies for enterprise compliance requirements.
GPU-optimized instances for demanding AI workloads
| Instance Type | GPU Configuration | Use Case | Typical Workload |
|---|---|---|---|
| p5.48xlarge | 8x NVIDIA H100 640GB HBM3 | Large Model Training | 70B+ parameter models, distributed training |
| p4d.24xlarge | 8x NVIDIA A100 320GB HBM2e | Production Inference | High-throughput LLM serving, fine-tuning |
| g5.48xlarge | 8x NVIDIA A10G 192GB GDDR6 | Cost-Optimized Inference | Smaller models, batch processing |
| inf2.48xlarge | 12x AWS Inferentia2 | Optimized Inference | High-volume, low-latency inference |
| trn1.32xlarge | 16x AWS Trainium | Custom Training | Cost-effective model training at scale |
Dynamic GPU cluster scaling based on inference queue depth and latency targets. Scale from 0 to hundreds of GPUs in minutes.
Elastic Fabric Adapter for ultra-low latency GPU-to-GPU communication. 400 Gbps bandwidth for distributed training workloads.
High-performance parallel file system for training data. Sub-millisecond latencies with S3 data repository integration.
Up to 90% cost savings with intelligent spot instance management. Automatic failover and checkpointing for fault tolerance.
Enterprise-grade security built into every layer
Complete visibility into your AI infrastructure
Native metrics, logs, and alarms. Custom dashboards for GPU utilization, inference latency, and token throughput.
Distributed tracing across agent components. Visualize request flows and identify performance bottlenecks.
ML-powered alerting for unusual patterns. Proactive notifications before issues impact users.
Detailed cost attribution by agent, environment, and resource type. Recommendations for optimization.
Let our team help you design the optimal infrastructure for your AI workloads.
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