New Way Now: Systalyze minimizes AI deployment costs with Google Cloud
12Featured in this video: Manya Ghobadi, CEO & Founder, Systalyze
Executive summary: AI deployment startup Systalyze helps organizations scale AI efficiently and make high-performance deployments radically more cost-effective. Systalyze’s technology uncovers and eliminates hidden cost drivers in how AI workloads interact with hardware, dramatically reducing the financial burden of AI deployment. Leveraging Google Cloud's infrastructure, including Google Kubernetes Engine (GKE), NVIDIA H100 GPUs, Artifact Registry, Cloud Storage, Gemini, and Vertex AI, Systalyze empowers customers to deploy cost-effective AI applications at scale. This partnership delivers significant business results, including two to 15x performance gains and 90% reduction in AI workload costs, all while maintaining strict data privacy.
Challenge: Most organizations face a high cost barrier to leverage AI, driven by inefficient resource consumption. These challenges often prevent enterprises from even beginning their AI journey, causing them to miss out on the transformative advantages that AI offers across operations, decision-making, and innovation.
Solution: Systalyze empowers organizations to begin and scale their AI initiatives by removing the cost and infrastructure barriers that typically hinder adoption. Its full lifecycle AI deployment platform uncovers inefficiencies and applies targeted optimizations to reduce costs. Using Google Cloud's advanced AI infrastructure, including GKE for containerized workflows and tools like Artifact Registry and Cloud Storage for efficient data management, Systalyze delivers flexible, infrastructure-agnostic solutions that make AI deployment radically more cost-effective while maintaining security and privacy, enabling organizations to adopt AI without prohibitive upfront investment.
Results: Systalyze has enabled up to a 90% reduction in AI costs for users, making advanced AI financially viable for a wider range of organizations. These cost savings are accompanied by substantial performance improvements, such as two to 15x performance improvements across various AI workloads. Customers across sectors, including healthcare and finance, have also realized faster model training, fine-tuning, inference, and agentic AI speeds and improved throughput, all while maintaining the privacy of their proprietary data.
Key Insights from Manya Ghobadi, CEO & Founder, Systalyze:
→ "Our mission at Systalyze is to democratize access to efficient AI by breaking down the high cost barriers that limit adoption. At Systalyze, we're making AI radically more efficient and cost-effective. We believe every organization should be able to deploy high-performing AI solutions without needing to become experts in infrastructure optimization or massive budgets."
→ "Our primary business challenge is helping our customers scale diverse AI workloads without incurring unsustainable costs. Google Cloud streamlines this process with easy-to-use infrastructure, particularly through Google Kubernetes Engine.”
→ “We value the seamless integration between Google Cloud's compute resources, Artifact Registry and storage buckets, which have significantly accelerated our workflow toward building effective customer solutions.”
→ "Systalyze is creating a new way to maximize AI performance while minimizing computational waste."
Google Cloud products used: GKE, NVIDIA H100 GPUs, Artifact Registry, Cloud Storage, Gemini, and Vertex AI