Engineering perspectives

What our team is thinking about before it becomes code, research, or product.

Insights
Scaling Parloa: When the platform becomes the product

Business expansion provides tremendous opportunities, and challenges. Read how Parloa's engineering overcome one of scaling's biggest hurdles with deployment stamps.

Ítalo Vietro

Abstract image with overlapping rainbow arcs and a rock formation, featuring the text "The latency paradox" at the bottom.
Insights
The latency paradox: Why voice AI speed is a budget, not a target

Parloa believes that for the most natural-sounding conversations, latency in AI agents should be assessed as a budget, not a a set target. Read why.

Kevin Boyer

Abstract grayscale waves with rainbow tones overlayed, featuring the text: "A look inside Parloa's Subtask Agents."
Insights
Multi-agent architecture: A look inside Parloa’s Subtask Agents

Most multi-agent work leverages supervisor LLMs at the routing layer. Multi-agent work for Voice AI requires an alternative approach. Learn how the architecture differs.

Robiert Luque Pérez

Hidden personalization layer in AI agents
Insights
The hidden layer of personalization in AI agents

Parloa's Agent Architect explains how linguistic style matching is permeating the AI agent space for more personalized customer experiences.

Rangina Ahmad

Parloa's Claude Kitchen
Insights
Agentic software engineering at scale: Parloa’s Claude Kitchen

95% of Parloa's code is written by AI. Learn what made the company transition to agent-written code and how we make it work.

Pedro Castillo

Insights
The engineer, reimagined: AI-driven development at Parloa

AI is rapidly transforming how software gets built at Parloa. Engineers are shifting from writing code to orchestrating AI agents that generate, review, and refine it. In this new model, developers focus less on implementation and more on guiding workflows, setting guardrails, and ensuring quality.

Nuno Marques and Masashi Beheim

Insights
Building customer-facing data products: A builder’s perspective

At Parloa, our AI agents drive high-stakes customer interactions, which demands a data platform designed for resilience. This article gives an overview on the architecture and governance principles we’ve implemented to meet this challenge.

Elisabeth Reitmayr

Insights
GPT-5.2 doesn’t just follow instructions, it follows through

There’s a specific kind of model failure we like to track closely. It doesn’t show up in latency graphs or user feedback. It sounds like the system is doing the right thing. It looks like it’s doing the right thing. And yet: the action never happens.

Anjana Vasan

Insights
What happens when calls never end?

Every customer conversation has a rhythm: a start, a middle, and (generally) an end. But what happens when it doesn’t?

Anjana Vasan and Mariano Kamp

Work with us

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