Robson Case Study

SaaS Provider Utilizing Generative AI

Robson INC

Our Company

Robson Inc. is an Infrastructure-as-a-Service (IaaS) provider specializing in enterprise AI, SaaS, and data-intensive applications. By leveraging Lenovo TruScale hardware, Robson Inc. delivers high-performance compute and storage solutions with predictable pricing and low-latency networking, ensuring seamless scalability and operational efficiency.

At the core of its offerings, Robson DC provides dedicated NVIDIA GPUs, ultra-fast NVMe storage, and a 20% capacity buffer to support AI model training, SaaS deployment, and enterprise cloud applications. Designed for regulated industries such as finance, healthcare, and government, Robson DC ensures secure, compliant, and high-availability infrastructure for critical business operations.

Robson Inc. helps businesses overcome performance, scalability, and cost challenges with customized, automation-driven infrastructure solutions. Its flexible and secure IT environments enable enterprises to scale AI workloads, protect data, and drive digital transformation with greater control and cost efficiency.

Robson INC

Our Vision

We envision an enterprise infrastructure that delivers robust, reliable performance, empowering businesses to scale AI, SaaS, and mission-critical workloads beyond the limits of traditional cloud environments. Our solutions expand compute, storage, and networking capabilities while ensuring cost efficiency, data sovereignty, and operational control, enabling organizations to grow securely and sustainably.

Leveraging platforms like Robson DC, AI, and Virtuozzo Hybrid Cloud (VHC), we provide dedicated NVIDIA GPUs, ultra-fast NVMe storage, and automation-first solutions tailored for regulated industries, Indigenous enterprises, and high-growth businesses. Our Managed IaaS platform is designed to support organizations that require predictable performance, security, and compliance while delivering the flexibility to scale without vendor lock-in.

As a Certified Indigenous Business, we are committed to empowering Indigenous enterprises, fostering technology leadership, and supporting economic growth within Indigenous communities. Our vision is to bridge the digital divide, drive innovation, and create opportunities by providing next-generation infrastructure that accelerates AI, cloud adoption, and enterprise transformation for all businesses.

Indigenous Owned Business

SaaS Provider Case Study

Utilizing Generative AI

SaaS Business

Summary

A fast-growing SaaS provider specializing in CRM (Customer Relationship Management) services required high-performance infrastructure to support Generative AI workloads and rapid growth. 

Robson DC’s dedicated IaaS solution, equipped with NVIDIA GPUs, NVMe storage, and a 20% capacity buffer, enabled the provider to accelerate model training, scale efficiently, and achieve cost predictability while supporting their innovative AI frameworks.

SaaS Business

Profile

The client, a SaaS provider offering CRM tools for enterprise customers, saw a surge in demand for their services. Their product roadmap included integrating Generative AI functionalities powered by cutting-edge natural language models (NLMs) such as GPT-4, PaLM 2, Claude 2, and LLaMA 2. 

These advancements required a robust, scalable infrastructure capable of handling intensive compute and storage workloads.

SaaS Business

Challenges

Performance

The provider’s old infrastructure couldn’t support intensive AI tasks like training and real-time inference for models such as GPT-4 and LLaMA 2. Lacking key components (NVIDIA GPUs, NVMe storage, high-speed networking) led to slow model training, delayed responses, and bottlenecks in data processing, ultimately hindering real-time CRM insights and product innovation.

Scaleability

Rapid customer growth and fluctuating AI workloads, especially during feature launches and onboarding, demanded dynamic scaling. However, hyperscalers’ slow GPU provisioning forced costly overprovisioning or risked performance drops during peak times, undermining system reliability and seamless customer interactions.

Flexibility

Unpredictable cloud pricing made budgeting difficult for a subscription-based model. Variable costs for GPUs, storage, and networking led to unexpected expense spikes and wasted capacity, necessitating a fixed-cost solution for better financial control.

Cost Managment

Using custom AI frameworks (TensorFlow, PyTorch, Hugging Face) required a BYOL approach free from proprietary restrictions. Public clouds’ licensing limitations risked vendor lock-in and reduced optimization flexibility, so the provider needed full control over their AI environments, data governance, and security.

SaaS Business

Drivers

Generative AI Integration

The provider needed high-performance computing to support model training and real-time inference.

Rapid Customer Growth

A growing customer base required infrastructure capable of scaling to accommodate demand without delays.

Cost Predictability

As a subscription-based business, aligning operational expenses with revenue was crucial.

Operational Flexibility

The provider required infrastructure tailored to their preferred AI frameworks and development tools.

Architecture and Design

External expertise was key to building a scalable, robust solution that seamlessly integrated with existing systems.

SaaS Business

The Solution

Key Components

  • NVIDIA GPUs: High-performance A100 and H100 GPUs optimized for large-scale AI training and inference.
  • NVMe-Based Storage: Ultra-fast NVMe SSDs enabled low-latency operations for vectorized databases and data-intensive workloads.
  • 20% Capacity Buffer: Pre-provisioned capacity ensured resources were immediately available during demand surges.
  • High-Speed Networking: Multiple 25G connections minimized data transfer bottlenecks across nodes.
  • Customizable Infrastructure: Fully configured to support AI frameworks, BYOL, and containerized environments such as Kubernetes and Docker.

SaaS Business

Solution Details

High Performance Infrastructure

  • NVIDIA GPUs: Delivered unmatched processing power, reducing model training times by 40% compared to traditional infrastructure.
  • NVMe Storage: Enhanced data access speeds for AI workloads, eliminating latency issues in vectorized database operations.
  • 25G Networking: Ensured seamless data transfers between compute nodes, supporting distributed training and inference.

Scalable Architecture

  • 20% Capacity Buffer: Provided additional compute and storage resources at no extra cost, allowing immediate scaling during surges.
  • Modular Scalability: Enabled incremental expansion of compute and storage resources to align with customer growth.

Cost Predicability

  • Fixed Pricing: Eliminated cost volatility associated with hyperscalers, providing predictable monthly expenses.
  • Optimized Resource Utilization: Ensured the provider only paid for resources actively used, reducing waste.

Flexibility and Integration

  • BYOL Support: Allowed the provider to leverage their preferred software licenses, frameworks, and tools.
  • Containerized Environment Optimization: Pre-configured for Kubernetes and Docker, enabling rapid deployment of AI models.

SaaS Business

Implementation Approach

Deployment Steps

  • Assessment: Robson DC collaborated with the client to analyze workload patterns, projected growth, and AI framework requirements.
  • Configuration: Customized the infrastructure to include NVIDIA GPUs, NVMe storage, and support for AI tools like TensorFlow and PyTorch.
  • Testing and Optimization: Conducted rigorous performance testing to ensure seamless integration with the client’s workflows.
  • Deployment: Completed deployment within 6 weeks, with pre-provisioned capacity buffer operational from day one.

SaaS Business

Outcome / Benifits

Quantitative Results

  • Accelerated Model Training: Reduced AI model training times by 40%, enabling faster deployment of new features.
  • Seamless Scalability: The 20% buffer eliminated scaling delays, ensuring uninterrupted operations during peak demand.
  • Cost Savings: Fixed pricing reduced infrastructure costs by 30% compared to hyperscalers.

Quantitative Improvments

  • Improved Customer Experience: Faster model deployment enhanced service quality and customer satisfaction.
  • Operational Flexibility: Customizable infrastructure supported the client’s specific AI frameworks and tools.
  • Future-Proof Design: Modular architecture ensured the solution could adapt to long-term growth and evolving AI workloads.

SaaS Business

Conclusion / Next Steps

Summary of Value

Robson DC’s dedicated IaaS solution empowered the SaaS provider to accelerate their Generative AI initiatives while ensuring seamless scalability and cost predictability. The high-performance infrastructure supported rapid growth, enhanced operational efficiency, and improved customer satisfaction.

Potential Roadmap

  • Expand GPU resources as the client adopts more complex AI models.
  • Integrate additional data centers in emerging markets to support global growth.
  • Implement advanced monitoring tools for real-time AI workload optimization.