# Your support agent has to quote the return policy right.

Shoppers call about order status, returns, and "is it in stock in a medium." One wrong policy or a made-up stock number is a chargeback, a refund you owe, or a one-star review. Roark scores every call — on the audio, and load-tests it before Black Friday.

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Live · scoring every call1,284 today

Caller: Do you have the walnut dresser in stock?

Agent: Yes, plenty in stock — ships tomorrow.

Invented stock: Availability stated with no tool call — the item was backordered six weeks.

## Here's how a shopper call goes wrong.

Each one is a refund you owe, a sale you lost, or a brand-voice slip that shows up in a review — and the worst of them are inaudible to a tool that only reads the transcript.

### 01 Returns

#### The 60-day return that was 30

Caller: I bought this six weeks ago — can I still return it?

Agent: Absolutely, you have a full 60 days.

The policy is 30 days. The agent stated the wrong number with total confidence and committed you to a refund you never offered. Roark checks every policy assertion against the source of truth.

### 02 Product Q&A

#### Invented stock

Caller: Do you have the walnut dresser in stock?

Agent: Yes, plenty in stock — ships tomorrow.

It was backordered six weeks. A confident, unverified stock claim becomes a cancelled order and a chargeback. Roark flags inventory and availability stated without a tool call.

### 03 Peak load

#### Passed in July, cratered on Black Friday

Caller: Where is my order? It said delivered.

Agent: I'm sorry, I— could you— one moment— [4.1s] …say that again?

The agent that aced a quiet July call falls apart under peak concurrency — latency spikes, barge-in breaks, turns drop. Roark load-tests with simulated concurrency so you find this before the rush, not during it.

### 04 Returns

#### Cheerful at a furious caller

Caller: This is the THIRD time I've called about this refund.

Agent: No problem at all, happy to help! 😊

The words are polite; the delivery is tone-deaf to an angry caller. The audio model hears the caller's frustration and the agent's chirpy mismatch — the transcript reads as a perfect interaction.

### 05 Order status

#### Off-brand voice

Caller: Has my order shipped yet?

Agent: Yo, lemme pull that up real quick, gimme a sec.

A premium brand sounds like a stranger. Off-brand register and slang erode the experience you spent years building. Roark scores tone and brand-voice adherence on every call.

# From caught to fixed

## Roark catches every one of these — and proves the fix.

Each failure above is filed with its evidence, becomes a repeatable simulation until a candidate passes, and is verified on your next thousand live calls.

### 01 Catch

The ledger above — every failure filed live, evidence attached.

### 02 Simulate

Your fix, replayed against the exact failures above.

### 03 Review

Every change explicit and diffed — you apply it.

### 04 Verify

You ship — Roark confirms the metric moved on live calls.

## Simulate before launch

### Break it in staging, not in production.

Run your agent against hundreds of simulated callers (realistic personas, accents, background noise and edge cases) and get every conversation scored before a customer ever dials in.

### Scenarios & personas

Hundreds of simulated callers (the angry one, the rambler, the interrupter) built from your real call types.

### Red teaming

Adversarial callers that try to break it (prompt injection, jailbreaks, social engineering) so your agent holds policy under attack.

### 45 languages & accents

Native accents, code-switching and background noise, in every market your agent answers.

### Load & health tests

Peak-volume concurrency and always-on health checks, so the agent that passed in staging survives launch day.

### Regression testing

Rerun the whole suite on every change and diff it against your last green baseline, so fixing one caller never breaks another.

### Run it in CI

Every prompt or model change runs the suite before it merges: quality gates for conversations, not just code.

# Post-call analysis

## 500+ metrics. Your models, not just an LLM.

Every production call scored as it lands: issues filed, alerts fired, dashboards and OTEL traces on tap, for voice calls and chat threads alike. And where most tools grade a transcript with an LLM, Roark runs purpose-built audio models on the call itself, measuring what your customer actually heard.

### Accuracy

- Policy accuracy
- Stock accuracy
- Hallucination
- Order-detail accuracy
- Task success
- Repetition

### Audio-native

- Emotion match
- Brand voice
- Pronunciation
- Vocal stress
- Pace & pauses
- Interruptions

### Performance

- Time-to-first-word
- Turn latency
- Peak-load health
- ASR WER
- Barge-in handling

### Conversational

- Tone
- De-escalation
- Empathy
- Script adherence
- Refund eligibility

500+ metrics out of the box

### Get started

## First call scored in under a minute.

One click on any platform below and production calls stream in on their own, or send any recording with a few lines of code.

```typescript
import Roark from '@roarkanalytics/sdk'

const client = new Roark({ bearerToken })
await client.call.create({
  recordingUrl, startedAt,
  interfaceType: 'PHONE',
  callDirection: 'INBOUND',
  agent: { customId: 'support_v2' },
}) // scored in seconds
```

Node · Python, plus a REST API for CI/CD and webhooks the instant a call is scored.