Neon Health builds AI-powered tools for patient access. Their AI workforce automates benefit verification, prior authorization, financial assistance, and care coordination, the manual workflows that block patients from getting treatment. They have saved over 2 million human hours across their customer base, cutting processing time in half and reducing costs by 80%.
For Neon Health, voice infrastructure is the product. Their AI agents call insurance providers, navigate phone trees, verify coverage, and secure authorizations on behalf of patients and healthcare hubs. When a call does not connect or latency disrupts the conversation, a patient waits longer for care.
When Twilio could not keep up with production AI call volume
Neon Health was running on Twilio. As their AI workforce scaled, the limits of a bolted-on voice stack became impossible to ignore.
Their agents handle complex multi-turn phone interactions: listening to hold music, navigating IVR menus, responding to prompts, and extracting information in real time. This requires consistently low latency across the full voice pipeline, from dialing to transcription to inference to synthesis. On Twilio, latency compounded at each handoff. Calls that should have taken seconds to route instead introduced delays that broke the conversational flow AI agents depend on.
The deeper problem was operational. Debugging a failed call meant correlating logs across separate telephony and AI layers. Scaling meant hoping each vendor kept up. Costs were unpredictable, and accountability was diffuse: when something broke between the telephony layer and the AI layer, no single vendor owned the problem.
Neon Health needed infrastructure built for production AI workloads, not repurposed telecom APIs.
One platform instead of five vendors
The evaluation came down to ownership. Twilio optimized for the demo: plug in an API, make a call. But production voice AI does not run on demos. It runs on infrastructure where telephony, speech processing, and inference are one operational domain, not three vendors pointing fingers.
Neon Health also evaluated Vonage, but neither could match what Telnyx Voice AI Agents offered: a single integrated stack where the call, the transcription, the inference, and the speech synthesis all happen in one place.
Neon Health selected Telnyx based on connectivity quality, coverage, developer experience, and the unique combination of capabilities that no single competitor offered. The buying experience itself was a signal. Telnyx understood what it meant to run AI voice agents in production, not just to place programmable calls.
From Frankenstack to single-stack: the Neon Health migration
With Telnyx, Neon Health were able to consolidate onto a single platform. Telnyx Inference hosts the frontier open-weight LLMs that power each conversation. The Voice API manages session state, call transfers, and IVR navigation. Real-time communication capabilities support live agent handoff when the AI encounters edge cases it cannot resolve.
What previously required coordinating across multiple vendors now runs on one platform. One set of logs. One latency budget to optimize instead of three.
Scaling AI agents across the patient access journey
Neon Health recently raised $6M to expand their AI workforce across more patient access workflows. With voice infrastructure that scales with demand, they can add new AI agent capabilities without rearchitecting their stack or negotiating new vendor contracts.
Neon Health is redefining patient access. Telnyx is supplying the real-time infrastructure scaling AI Agents requires.
