Speech-To-Text
Real-time voice AI agents are among the most demanding applications in modern software engineering. Unlike traditional request-response systems, where latency can be measured in hundreds of milliseconds, voice agents must maintain the illusion of natural human conversation.
Speech-To-Text
The large language model sits at the heart of every modern voice agent. Speech-to-text and text-to-speech handle the audio, but the LLM fundamentally determines how intelligent, helpful, and natural your agent feels to users.
Speech-To-Text
The promise of voice AI for customer service is compelling. We now have intelligent agents that can handle inquiries, update records in real-time, and provide instant access to critical business data.
Speech-To-Text
As voice agents become a core part of customer and employee experience, users need to know these AI systems are accurate, safe, and acting within boundaries. That’s especially true for enterprise-grade tools, where a rogue voice agent can severely damage relationships and create major legal risks.
Speech-To-Text
The call center business model has worked well for decades. BPOs supply agents to client companies who pay by the seat or by the hour. More hours means more revenue, and growth inevitably relies on scaling headcount.
Speech-To-Text
Businesses expanding globally face an immediate language barrier. Customers want service in their native tongue, but most companies and call center providers don’t have enough multilingual agents to meet that demand.
