The Secret to Eliminating Latency in Voice AI 🔧

2026-03-23 · Source: AssemblyAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

Trellis, a YC Winter 22 voice AI company, specializes in high-volume voice applications, including outbound parallel dialers and inbound voice agents. The company emphasizes redundancy and scripting for its voice agents, particularly for clients with precise communication requirements. Trellis observes that while some users initially desire unscripted, creative AI responses, serious business clients demand exact phrasing due to its impact on their operations. To meet this need, Trellis prioritizes pre-scripting agent responses to minimize "creativity" and ensure precise word delivery. This approach allows for offline speech generation, reducing real-time dependencies on text-to-speech vendors and improving system reliability, especially for non-live applications.

Key takeaway

For Directors of AI/ML overseeing high-volume voice agent deployments, prioritize pre-scripting and offline speech generation. This strategy ensures message precision, reduces reliance on real-time text-to-speech services, and significantly enhances system redundancy and reliability, especially for critical business communications where exact phrasing is paramount.

Key insights

High-volume voice agents benefit from scripting and redundancy to meet precise business communication needs.

Principles

• Scripting enhances reliability.
• Precision matters more than creativity.

Method

Pre-scripting voice agent responses and generating speech offline reduces real-time vendor dependencies and improves redundancy for non-live applications.

In practice

• Pre-render common agent responses.
• Cache speech generation outputs.

Topics

• Voice AI Systems
• Trellis
• Voice Agents
• Latency Reduction
• Scripted Interactions

Best for: AI Engineer, NLP Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by AssemblyAI.