Millions of AI assets monthly demanded enterprise moderation. Alibaba Cloud's stack delivered 99.5%+ accuracy, no custom model needed.
A US-based startup offering students, researchers, and creators an all-in-one platform for AI chat, image generation, and video creation, producing millions of AI-generated assets monthly.
Delivering image and video generation required massive computational power with low-latency performance at this scale. Preventing harmful outputs...
“Alibaba Cloud has helped us to rapidly acquire market users while effectively mitigating risks through their robust AIGC services, large language models, and generative AI security capabilities.”
All-in-one AI assistant for study, work, and creativity with various generative tools.
Cloud computing and artificial intelligence platform for global enterprises.
EaseMate's Content moderation is part of this use case:
Related implementations across industries and use cases
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Designers manually browsed thousands of files to find assets. Now, AI lets them locate components via text or screenshots.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Manual review slowed a viral Vogue contest. AI took over to moderate 56,000 entries, saving two weeks of editorial effort.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
Millions of AI assets monthly demanded enterprise moderation. Alibaba Cloud's stack delivered 99.5%+ accuracy, no custom model needed.
A US-based startup offering students, researchers, and creators an all-in-one platform for AI chat, image generation, and video creation, producing millions of AI-generated assets monthly.
Delivering image and video generation required massive computational power with low-latency performance at this scale. Preventing harmful outputs...
“Alibaba Cloud has helped us to rapidly acquire market users while effectively mitigating risks through their robust AIGC services, large language models, and generative AI security capabilities.”
All-in-one AI assistant for study, work, and creativity with various generative tools.
Cloud computing and artificial intelligence platform for global enterprises.
EaseMate's Content moderation is part of this use case:
Related implementations across industries and use cases
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Designers manually browsed thousands of files to find assets. Now, AI lets them locate components via text or screenshots.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Manual review slowed a viral Vogue contest. AI took over to moderate 56,000 entries, saving two weeks of editorial effort.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.