Complexity slowed AI adoption. Intelligent orchestration on GKE now deploys models in minutes, allowing clients to iterate 90% faster.
An enterprise AI platform founded by MIT researchers enables organizations to deploy fine-tuning, inference, and agentic applications across diverse computing environments.
Enterprises struggled with the high complexity and unpredictable costs of AI adoption, often risking millions with uncertain returns. The platform...
“Our mission at Systalyze is to democratize access to efficient and affordable AI by eliminating the complexity and cost barriers that keep most organizations from getting started. We believe every organization should be able to deploy high-performing AI solutions without incurring unsustainable costs. Our platform streamlines the entire AI lifecycle, reducing costs by 90%.”
AI workload optimization platform for compute efficiency and cost reduction.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
$98/hr training costs blocked custom AI. Moving to bare-metal GPUs cut costs 7x, enabling models that slashed chart review times by 80%.
Self-hosting GPUs capped training at weekly runs. A serverless shift cut costs 3x and enabled daily iteration for 87% accuracy.
Nurses manually reviewed charts for risk. AI now automates stratification, launching a diagnostic tool in 12 months vs years.
Manual triage meant urgent faxes sat for days. AI now routes millions of documents to 1,200+ destinations in seconds.
Manual segmentation took 20 minutes, delaying care. AI now analyzes hemorrhages in seconds, aiding decisions across 23 regional sites.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.