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Vertical Data

AI Consulting

Overview

Navigating the AI infrastructure landscape can be complex. Our AI Consulting Service helps businesses identify use cases as well as the right hardware, software, and deployment strategies to power their AI workloads efficiently. Whether you’re building large-scale AI training clusters, optimizing inference at the edge, or deploying hybrid AI solutions, we provide expert guidance to ensure you infrastructure aligns with your business goals—maximizing performance, scalability, and cost-efficiency.

Key Features & Specifications

  • Ai use case identification, definition, development and deployment

  • AI Infrastructure Assessment – Evaluate your current compute environment and recommend the best GPUs, accelerators, and cloud/on-prem solutions

  • Extreme Computational Power – Supports 64 AMD, NVIDIA GPUs and custom PCIe accelerators

  • Custom AI Hardware Selection – Match your AI workloads to the right NVIDIA, AMD, and specialized AI accelerators (H100, MI300X, TPU, SpeedAI, etc.).

  • Edge vs. Cloud AI Strategy – Determine the best deployment model for latency, cost, and performance optimization.

  • Power & Cost Efficiency Analysis – Optimize AI infrastructure for total cost of ownership (TCO), power consumption, and operational efficiency

  • AI Model Performance Benchmarking – Test and refine models on different hardware setups to ensure optimal inference/training performance.

 

Performance & Scalability

  • Right-Sized AI Compute – Avoid over- or under-provisioning with tailored AI infrastructure recommendations.

  • Future-Proof AI Strategy – Ensure compatibility with next-gen hardware (H200, MI300X, PCIe-based architectures)

  • Scalable AI Solutions – Design modular, expandable AI clusters to accommodate growing workloads.

  • Workload-Specific Optimization – Fine-tune LLM training, real-time inference, and AI-powered analytics for peak performance.

Security & Compliance

  • Enterprise-Grade AI Security – Ensure AI compute and data governance align with compliance regulations.

  • Data Privacy & Sovereignty – Define infrastructure strategies for secure, region-specific AI model training.

  • Zero-Trust AI Compute – Implement security-first AI infrastructure with hardware-based encryption and secure boot mechanisms.

  • Industry-Specific Compliance Guidance – Ensure AI solutions meet regulatory requirements in finance, healthcare, and government AI.

Integration & Compatibility

  • Vendor-Neutral Guidance – Recommendations across on-prem, colocation, hybrid cloud, and multi-cloud AI deployments.

  • AI Stack Interoperability – Ensure seamless integration with NVIDIA CUDA, ROCm and open AI frameworks.

  • MLOps & Workflow Automation – Optimize AI pipeline deployment with Kubernetes, Ray, and MLflow orchestration.

  • Security & Compliance Alignment – Configure AI environments to meet SOC 2, ISO 27001, HIPAA, and GDPR standards.

Industries & Use Cases

  • Enterprise AI Strategy & Infrastructure Planning – Align business AI objectives with the right hardware/software choices.

  • AI-Powered SaaS & Startups – Guide fast-scaling AI SaaS companies on cost-effective, high-performance infrastructure.

  • AI-Powered SaaS & Startups – Guide fast-scaling AI SaaS companies on cost-effective, high-performance infrastructure.

  • Healthcare & Life Sciences AI – Advise on medical imaging AI, drug discovery compute, and genomics acceleration.

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