Engineers lost a week manually configuring each training environment. Now, they spin up instances in one hour.
A technology provider serving 3.35 million users through 720 enterprise customers across Asia with custom chatbot and text analysis solutions.
Engineers spent a full week setting up each training environment due to complex software compatibility issues, while legacy GPUs lacked the memory...
“We've been improving our machine learning (ML) models for years to help companies process text more efficiently and provide better automated customer services. Our hyper realistic virtual assistants can be customized for various usage scenarios, and our customers are able to adopt them easily without having any programming or data organization skills.”
On-premise AI platform for private LLM deployment and knowledge management.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
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Infrastructure maintenance distracted engineers. Migrating to Google Cloud cut release cycles from one month to two weeks.
Engineers manually provisioned servers during spikes. Automated GPU scaling now cuts user waits from days to seconds.
Training human-sounding voices took 20 days on three servers. With H100s, cycles dropped to 5 days on one server, scaling 18 languages.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
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.