Visualsoft’s AI rendering stack on-premise went down under peak sales traffic. They used cloud migration services to migrate their workloads to the cloud-native architecture with auto-scaling GPU clusters, edge caching, and cloud security services, supporting up to 40,000 concurrent requests and zero downtime, with no reduction in the quality of the render during peak traffic events.

Built a generative AI automation system for large-scale content & data generation automation. The solution improved the speed of production by 3X, reduced the manual workload by 65%, and improved the output consistency across high-demand operational processes.

Cypress was losing hours daily to manual review cycles in their logistics workflows. We built a predictive ML engine trained on three years of operational data, capable of forecasting demand shifts and auto-routing decisions without human intervention.

Capmark’s dated loan portal had users dropping off halfway through the application process and support teams were overwhelmed by simple questions. We redeveloped it with an embedded AI assistant to guide clients through document submission, surface relevant products, and answer questions in real time.

It was a hard slog for Infotech engineers to work thru years of internal documentation and they would send repetitive questions to senior staff. In our enterprise AI model deployment process, we did foundation model fine-tuning over their entire knowledge base and integrated with their ticketing system. New engineers were up to speed in days. Senior staff weren’t pulled into unnecessarily escalated issues.

A research division at UCLA was spending more time looking than researching, manually cross-referencing thousands of academic papers and clinical records. We built a custom LLM trained on their research corpus with Enterprise LLM integration to answer multi-part queries, summarize findings across documents, and respect per-document access permissions for authorized researchers only.