Problems / AI products, hard

Medical scribe: redaction bottleneck

A medical scribe transcribes visits, redacts PII and drafts notes. The redactor has 1 vCPU and 20 ms per note, at 100 notes a second.

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Your goals

Success ≥ 99%, p99 ≤ 5 s.

The traffic

100 requests a second for 30 seconds: 100% request (reads).

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic enters here.Calls AI app.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header.–
AI appApp serviceLoad balancer forwards to it.Calls Speech to text, PII redactor, GPU serving pool.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s.3 replicas × 500 slots · timeout 30 s
Speech to textSpeech to textAI app calls it.Streaming speech recognition returns partial words while the user is still talking.400 slots · 6,000 calls/min
PII redactorPII redactorAI app calls it.Redacting personal data before it reaches a model or a log reduces privacy and compliance risk.100 slots
GPU serving poolSelf-hosted serving poolAI app calls it.GPU servers batch requests together; throughput rises with batch size until memory runs out.400 slots

Hints

Try it first. Open one hint at a time if you get stuck.

Hint 1

CPU needed = 100 × 20 ms = 2 vCPUs.

Hint 2

Find the red card first, then its capacity: slots ÷ seconds per request.

One way to solve it

Give the PII redactor more capacity and CPU.

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