Universal-3 Pro by AssemblyAI — Speech-to-text that finally understands context
Speech-to-text that finally understands context
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While researching AI, I realized most startups and developer teams struggle to train accurate LLMs because they lack high-quality labeled data. When I was building my own AI agents, I tried several annotation tools; most were slow and complex. Even AI-assisted platforms are too expensive to process data, and many tools were so technical that non-technical founders couldn’t even use them easily.
After speaking with fellow AI researchers and founders, I found the same issue everywhere: data annotation was the bottleneck. That’s when I decided to build Ateegnas, a fast, cost-efficient, and easy-to-use annotation platform powered by multi-agent AI orchestration, so both technical and non-technical teams can label data seamlessly
While researching AI, I realized most startups and developer teams struggle to train accurate LLMs because they lack high-quality labeled data. When I was building my own AI agents, I tried several annotation tools; most were slow and complex. Even AI-assisted platforms are too expensive to process data, and many tools were so technical that non-technical founders couldn’t even use them easily.
After speaking with fellow AI researchers and founders, I found the same issue everywhere: data annotation was the bottleneck. That’s when I decided to build Ateegnas, a fast, cost-efficient, and easy-to-use annotation platform powered by multi-agent AI orchestration, so both technical and non-technical teams can label data seamlessly
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Congratulations on your launch. What kind of data modalities does it support?
@tham_yikfoong Thanks Buddy ,For now we are starting with text only ,once we scale we will move further to multimodal.