Blog - Ingeniería
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.
Crafting a Natural-Sounding AI Voice
Go behind the scenes of Signal, Cresta’s AI concierge, and explore the technical foundations that power its conversational experience.
Evaluating AI Voices – What Does It Mean to Sound “Good”?
"Your AI Agent doesn't sound good"—this critique is perhaps the deepest dread for anyone building a voice agent.
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.
Building and Deploying Production‑Grade AI Agents: Cresta’s End‑to‑End Approach
In this post, we walk through Cresta’s full lifecycle for building and deploying production-grade AI agents.
Why You Can’t Trust Out-of-the-Box Evaluators
Generic AI evaluators promise plug-and-play accuracy—but fall short where nuance and domain context matter most. This post breaks down why out-of-the-box LLM evaluators mislead enterprise teams, how misalignment erodes trust, and how Cresta’s expert-aligned, transparent evaluation framework turns measurement into a foundation for reliable AI performance.
The New Perimeter is Your Contact Center: Why Observability Now Belongs in Your Tech Stack
This post explores why observability—seeing what’s happening inside every conversation and workflow—is now essential for security. Learn how Cresta’s real-time intelligence, behavioral insights, and in-the-moment guardrails shrink the gray space where fraud and insider abuse thrive.
Engineering for Real-Time Voice Agent Latency
Discover how Cresta’s team optimizes every millisecond—from telephony and ASR to LLMs and TTS—to deliver real-time, human-like conversations at scale.
When to Use What: A Practical Guide to AI Agent Testing and Evaluation
Learn the sequencing approach to best understand when to use which testing and evaluation method for the most effective assessment of your AI agents.
The New World of Non-Deterministic Testing and Evaluation
In the early days of conversational AI, testing and evaluation were fairly predictable. Flow-based bots followed strict, pre-defined paths, so teams could simply simulate each step and confirm that every interaction point returned the expected output.
AI-Ready Knowledge for Contact Centers: Closing the Gap Between the Knowledge Base and AI
Learn about Cresta's approach to transform knowledge bases into AI-ready knowledge that supports the modern contact center.
Cresta’s Three Strategic Pillars of AI Agent Defense for Enterprise Security and Compliance
AI agents can’t just be smart—they need to be safe. This post unpacks Cresta’s three-pillar guardrail framework, built to keep enterprise AI agents secure, compliant, and resilient from day one.
Voice AI Agents for Customer Experience: Why Decentralized Agent Architectures Can Outperform Central Orchestrators
Central orchestrators slow down and break under pressure. This blog explores why Cresta’s decentralized AI agent architecture delivers faster, more reliable customer experiences—without the single points of failure.
More than Just a Model: How Cresta Delivers Precise, Adaptable Summaries with Ultra-Low Latency
This post breaks down how Cresta built a system, from training data to model tuning, that delivers fast, high-quality summaries tailored to the realities of contact centers.
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