Roark for Retail — voice agent quality for order status, returns & product Q&A - Roark
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.
Backed by YC
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.
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.