Infrastructure maintenance distracted engineers. Migrating to Google Cloud cut release cycles from one month to two weeks.
An Australian AI startup provides a platform enabling global customers to build applications using over 90 different large language models.
Managing proprietary infrastructure diverted engineering talent from product innovation to low-value maintenance tasks. The existing setup could not...
“Traditionally, you need data scientists, complex models and detailed use cases to leverage AI, but the rapid development of generative AI has made deriving value from the technology much easier.”
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Local servers caused latency bottlenecks. Cloud AI now translates complex docs in days, cutting months from market entry timelines.
Complexity kept AI prototypes in the lab. Now, teams launch compliant apps in under one hour using a managed platform.
New document types took weeks of manual coding. GenAI cut setup to minutes, letting teams refine extractions via natural language.
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.