Engineering perspectives
What our team is thinking about before it becomes code, research, or product.
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How we built Parloa's model evaluation system
Parloa's AMP Dojo System allows scalable and reproducible experimentation and testing of different components of Parloa’s product.
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Red teaming conversational AI agents: How Parloa stress tests production deployments
Learn about red teaming, the testing methodology with an attack taxonomy, evaluation pipeline, and deliverables that bring secure conversational AI to all customers.
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The caller’s register: Why language habits outlast the technology that created them
Parloa's agent architect explains how IVR systems have designed a certain linguistic register that voice AI systems need to transform through trust-building experiences.
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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.
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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.
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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.
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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.
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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.
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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.
Work with us
Join Parloa to build what's next in artificial intelligence. We're always looking to work with the best and the brightest engineers and researchers.