Blog - Engineering
Introducing the Cresta CLI: A Developer Surface for an Agent-Operable Platform
AI coding agents are only as good as the surfaces they can reach. Cresta CLI puts the platform in your terminal. Read the blog to understand more!
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.
Grounding Reality – How Cresta Tackles LLM Hallucinations in Enterprise AI
Discover the six core pillars behind Cresta’s ground-breaking approach to building AI systems that minimize hallucinations by design, not by chance.
Build vs. Buy: How Cresta Engineered Its Own Customer Data Access Solution
Build vs. Buy: Which is the right choice for access management? Learn why Cresta's security team chose to build a custom customer data access solution instead of relying on third-party vendors.
Understanding Cresta’s Voice Platform - ML Services, Inference Graphs, and Real-Time Intelligence
Learn more about Cresta's voice platform's machine learning (ML) stack, exploring how inference graphs orchestrate model workflows, how customer-specific policies influence ML processing, and how Cresta delivers actionable insights in real-time.
Understanding Cresta’s Voice Platform - The Voice Stack
Read part two of our series focused on Cresta's voice platform, this time focusing on how the platform processes live audio streams through its voice stack and how business logic layers power real-time guidance for agents.
Understanding Cresta’s Voice Platform - Handling Incoming Traffic with Customer-Specific Subdomains
Learn about the technology behind Cresta's voice platform in this three-part series.
How fine tuned LLMs power knowledge assist, summarization, and chat suggestions
Learn about how Cresta is leveraging fine tuned LLMs to power knowledge assist, summarization, and chat suggestions in this latest post on our foundation model, Ocean.
Streamlining front-end development: Insights from Cresta’s tech stack
Take a close look at Cresta’s front-end (FE) architecture: how the main FE repository is structured, our build and deployment processes, and our approach to code generation.
John Donovan on the Potential of Large Language Models in the Enterprise
John Donovan, prior CEO of AT&T Communications, shares his c-level insights on deploying large language models in the enterprise.
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