Machine Learning Engineer
When the Call Runs Too Long: Modeling Outcomes for Long Conversations
In this post, we discuss four practical approaches for modeling outcomes on long conversations, each suited to different use cases and constraints.
How Cresta Scales Data Annotation With a Human-Supervised Multi-Agent System (MAS)
How do you scale high-quality data annotation without sacrificing rigor? In this post, we explore our multi-agent approach—combining multiple LLM annotators, structured deliberation, and human oversight—to replicate the discipline of expert human workflows at enterprise scale.
When Every Word Matters: Engineering Real-Time Multilingual Intelligence for Human Conversations
This technical deep dive unpacks the architectural decisions, latency optimizations, and model evaluation frameworks behind our Real-Time Translator (RTT)—showing how language detection, transcription, translation, and speech synthesis work together to enable seamless global communication.
How We Built a State-of-the-Art Research Agent for Call Center Conversation Analytics
Take a deep dive into how we built Cresta AI Analyst, and all of the lessons learned along the way.
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