Relay - Relay

Build custom artifact detection models

Relay is a developer platform for detecting audio artifacts in Voice AI output. Train custom models on your data, then run inference to find glitches, hallucinations, unnatural pauses, and other issues in your TTS audio.

Upload Audio

Upload labeled audio files to build your training dataset

Train Models

Train custom detection models on your annotated data

Run Inference

Detect artifacts in production audio with timestamped results

API Reference

Complete REST API documentation with examples

Quick example

Run inference on audio to detect artifacts:

curl -X POST https://api.relayai.dev/api/v1/inference-jobs \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model_id": "your-model-id",
    "config": {
      "threshold": 0.5
    }
  }'

import requests

response = requests.post(
    "https://api.relayai.dev/api/v1/inference-jobs",
    headers={"X-API-Key": "YOUR_API_KEY"},
    json={
        "model_id": "your-model-id",
        "config": {"threshold": 0.5}
    }
)
job = response.json()

const response = await fetch("https://api.relayai.dev/api/v1/inference-jobs", {
  method: "POST",
  headers: {
    "X-API-Key": "YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model_id: "your-model-id",
    config: { threshold: 0.5 }
  }),
});
const job = await response.json();

Detection results include timestamps and confidence scores:

{
  "detections": [
    {
      "artifact_type": "glitch",
      "start_ms": 1200,
      "end_ms": 1450,
      "confidence": 0.87
    },
    {
      "artifact_type": "long_pause",
      "start_ms": 3500,
      "end_ms": 4200,
      "confidence": 0.92
    }
  ]
}

How it works

Create a Dataset

Define the artifact types you want to detect (glitch, silence, hallucination, etc.)

Upload Audio

Upload labeled audio files in WAV, MP3, FLAC, or other common formats

Add Annotations

Mark where artifacts occur in each file with start/end timestamps

Train a Model

Submit a training job to build a custom model from your annotated data

Run Inference

Upload new audio files to detect artifacts using your trained model

Get started

Quickstart

Get up and running in 5 minutes

Authentication

Learn how to authenticate with the API

​Build custom artifact detection models

Upload Audio

Train Models

Run Inference

API Reference

​Quick example

​How it works

​Get started

Quickstart

Authentication

Build custom artifact detection models

Quick example

How it works

Get started