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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Engineering perspectives
What our team is thinking about before it becomes code, research, or product.
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Jev could be the missing decision layer for agentic CX
Large language models taught AI agents how to talk. System One models like Jev could teach them when to route, escalate, and act, and whether they succeeded.
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Building Parloa Zones: Repeatable regional deployments with central control
Adding a new region to Parloa used to take coordinated work across engineering teams. Learn how we built Parloa Zones, which lets customers run AI agents in the region they choose, so that standing up a new region is now largely automated.
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The A2B service layer: Why enterprises need one governed interface for personal agents
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What does it mean for a speech-to-speech model to understand a caller?
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Beyond go-live: How live conversations make great AI even better
Go-live isn't the finish line for voice AI. Learn how Parloa turns production conversations into evidence for continuous agent improvement.
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Who improves the agent that improves the agent? Harness engineering at Parloa
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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.