The emotional AI layer for every application.

# Submit a call recording
curl -X POST https://your-instance.sentientmachines.tech/api/investigate \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -F "file=@call-recording.wav" \
  -F "meta.customerRef=ACC-4471"

# → 201 Created
{ "jobId": "e424667a-c3fc-4563-9e2d-4be7db6743f4", "organization": "acme-corp" }

import os, time, requests

BASE = "https://your-instance.sentientmachines.tech/api"
H = {"Authorization": f"Bearer {os.environ['SENTIENT_API_TOKEN']}"}

job = requests.post(f"{BASE}/investigate", headers=H,
    files={"file": open("call.wav", "rb")}).json()

while requests.get(f"{BASE}/investigate/{job['jobId']}",
                   headers=H).json()["status"] == "RUNNING":
    time.sleep(5)

result = requests.get(f"{BASE}/investigate/{job['jobId']}/result",
                      headers=H).json()
print(result["metrics"]["emotion"]["eri"], result["tags"]["sentiment"])

const res = await fetch("https://your-instance.sentientmachines.tech/api/customer-profile", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.SENTIENT_API_TOKEN}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({ phone: "+447700900123", limit: 3 })
});
const profile = await res.json();
if (profile.deviationFlagged) {
  queueProactiveContact(profile.customerId, profile.trend);
}

# One agent's EHRI/AEHS performance and recent calls
curl -X POST https://your-instance.sentientmachines.tech/api/agent-profile \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"agentName": "Alex Rivera", "limit": 2}'

# → "ehriIndex": 108.4, "aehsIndex": 106.1, "status": "On Track", …