Four use cases. One architecture. Owned infrastructure that puts GPUs on your balance sheet instead of your cloud bill. Each offering is built on the same 5-Layer AI Cake — proven at Fortune 25 scale.
Every pharma enterprise processes clinical and regulatory documents at scale — prior authorisations, adverse event reports, clinical trial submissions. This offering replaces cloud GPU rental with an owned inference platform that processes thousands of documents daily at 40–60% lower cost, with absolute data sovereignty.
Gigapixel pathology slides, radiology scans, and manufacturing quality images generate massive data volumes that make cloud egress costs exceed compute costs. This offering deploys owned inference infrastructure — including edge compute at pathology labs — to eliminate data transit and deliver near-real-time diagnostic AI.
Most pharma enterprises have 5–8 departments independently renting cloud GPUs with no governance, no reuse, and 15–30% utilisation. This offering consolidates fragmented cloud GPU spend into one owned, namespace-isolated platform — serving every department from a single investment with 70–85% utilisation.
R&D teams pay $1M+ per year in commercial AI API fees to monitor patents and search literature — while leaking pipeline strategy through every query. This offering replaces external APIs entirely with a private, on-prem intelligence platform: continuous patent monitoring, corpus-scale literature analysis, and a scientist-facing Discovery Copilot, with every query invisible to the outside world.