Identify and prioritize AI use cases that align with business strategy, creating a focused path for implementation

Assess AI costs and needs, including Total cost of ownership (TCO) and Graphics processing unit (GPU) sizing to inform a cost-optimized AI infrastructure

Plan and design AI infrastructure addressing compute, storage, networking, scalability, security, and cost efficiency from core to edge

Provide advanced AI infrastructure for clients, including a detailed bill of materials for design and deployment

Set up and tune infrastructure components of AI environments, such as hardware, software, networking, and security

Validate, test, and verify that software is production and connection ready upon delivery

Apply standardized workloads to test compute performance, latency, and throughput of infrastructure components

Build E2E data flows to collect, clean, label, and feed data into AI models efficiently and compute environments

Deploy and configure AI software tools and frameworks to help enable efficient, scalable model operations

Deploy network defenses and security policies to safeguard data, models, and systems across AI infrastructure

Manage how compute intensive tasks are distributed across the infrastructure stack to maximize performance and cost efficiency

Manage and maintain the compute, storage, networking, and cost components across hardware environments

Manage and govern AI models to help ensure consistent, reliable, and secure operations without hallucinations or model drift

Fine-tune AI model parameters to maximize the performance of AI applications

Track system health and performance, alerting teams instantly to problems to ensure uninterrupted operations