Enterprise
Enterprises are experiencing a range of challenges in enabling the full benefits and value to be obtained from the adoption of AI Models across their activities.
AI workloads involve multiple models with unpredictable variables, ranging from request sizes and prompt complexities to fluctuating request rates. Because timing and load levels are hard to predict, systems must be designed to scale dynamically, delivering high performance during peak demand while remaining cost-effective at lower utilization.
Critical Success Factors for Providing Enterprise-level AI Services
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Maximize ROI
To maximize the return on investment, the maximum number of users need to be supported across a range of use cases, models, and services.
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Maximize Operational Efficiency
Services need to be provided in an operationally cost-efficient way, particularly token generation and management, with the ability to scale with user demand.
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Maximize Equipment Throughput
Maximize equipment used with support for multiple model types, enabling benefits across all stages of the Deep Learning Lifecycle.
Rivos Solution Benefits for Enterprises
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Flexibility
Enterprise AI services must operationalize generative AI and automate complex workflows to drive real business value. This requires the flexibility to adopt and deploy a wide range of models, tailored to specific customer needs, use cases, and performance requirements.
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Cost Efficiency
Enterprise cost-efficiency challenges can be addressed by reusing existing infrastructure, minimizing new hardware investments, and reducing energy consumption. This approach lowers the total cost of ownership (TCO), improves return on investment (ROI), and supports the deployment of scalable, sustainable AI solutions.
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Quality
A wide range of AI models are designed to enhance data quality, an essential foundation for trustworthy decision-making. Rivos integrates advanced Data Analytics capabilities directly into its platform, enabling seamless support for data-centric techniques like Fine Tuning, retrieval-augmented generation (RAG), and model training. As Enterprises increasingly rely on AI, ensuring the integrity of input data is critical to building confidence in the outputs. By unifying these capabilities, the Rivos platform delivers a comprehensive solution that consolidates data enhancement and model performance into a single, scalable system.
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Scalability
Enterprises need AI infrastructure that can adapt to unpredictable user growth and fluctuating workloads, without the inefficiency of overprovisioning. Rivos delivers elastic, on-demand performance that scales seamlessly to support both new and returning users. As use cases evolve and demand surges, Rivos ensures consistent, high-quality AI services while maximizing infrastructure efficiency and user satisfaction.