Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
A generative AI company building advanced voice models and deepfake detection tools for banking and law enforcement, dealing with datasets that ballooned to over 60 terabytes.
Engineers spent 90% of their time on manual data preparation and file transfers rather than model building, leaving high-performance accelerators...
“Google Cloud was the natural fit to modernize infrastructure with AI-optimized tools and architecture.”
Generative AI platform for voice cloning, text-to-speech, and deepfake detection.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
Building an agent took 50 people weeks of work. A bank now designs and tests the same tool in just four days.
Engineers manually provisioned servers during spikes. Automated GPU scaling now cuts user waits from days to seconds.
Self-hosting caused weekly outages and lag. Moving to Groq ended downtime and cut response times by 500ms, regardless of prompt length.
Engineers spent weeks manually configuring infrastructure. Now, they deploy pre-optimized models in minutes.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
A generative AI company building advanced voice models and deepfake detection tools for banking and law enforcement, dealing with datasets that ballooned to over 60 terabytes.
Engineers spent 90% of their time on manual data preparation and file transfers rather than model building, leaving high-performance accelerators...
“Google Cloud was the natural fit to modernize infrastructure with AI-optimized tools and architecture.”
Generative AI platform for voice cloning, text-to-speech, and deepfake detection.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Related implementations across industries and use cases
Building an agent took 50 people weeks of work. A bank now designs and tests the same tool in just four days.
Engineers manually provisioned servers during spikes. Automated GPU scaling now cuts user waits from days to seconds.
Self-hosting caused weekly outages and lag. Moving to Groq ended downtime and cut response times by 500ms, regardless of prompt length.
Engineers spent weeks manually configuring infrastructure. Now, they deploy pre-optimized models in minutes.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.