Engineering blog

Building reliable AI.

Field notes on the parts that don't fit in a demo — latency budgets, evals, voice agents, and RAG that holds up in front of real users.

Voice AI · Latency

Sub-250ms, or it isn't a conversation

Why end-to-end voice latency is the whole game — and how to get under the threshold where a call starts to feel human instead of like a walkie-talkie.

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Voice agents · Reliability

Teaching an AI to beat a payer phone tree

IVRs are hostile, all different, and change without warning. Why we treat them as a control problem with a state machine — not a chat problem.

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Clinical AI · Evals

The double-dose problem

Making an agent ask the right question, not just answer one — and the evals against real transcripts that prove it caught the thing that mattered.

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RAG · Cost & speed

RAG that doesn't fall over in production

Grounding every claim to a source, an eval harness that catches regressions, and pushing the hot path onto cheaper models without losing quality.

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Voice AI · Architecture

The listener constellation: one voice, a dozen AIs

A swarm of specialized listeners watching one transcript in parallel, each able to inject context through a four-level priority queue — up to an immediate interrupt.

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Clinical AI · Supervision

The nurse is the law

Human-supervised AI as architecture, not a compliance checkbox bolted on at the end — and why the constraint is what makes the rest possible.

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Data · Moats

The data layer: what you own when you own the calls

Own the operator, own every interaction — a longitudinal record that compounds, plus per-patient fine-tuning on what actually works.

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Agents · Orchestration

The work happens while you're still talking

Background agents that book, refill, notify, and document — silently, mid-conversation, six at once, without colliding.

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Integration · RPA

Documenting into any EHR without an integration project

A browser agent that uses the EHR the way a nurse does — no API, no vendor sign-off. Days, not quarters.

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