Voice AI Evaluation Tools in 2026: 8 Platforms Compared, and What to Test Before You Pick One

Say you run a booking agent for a dental clinic. Your team edits one line of the prompt so the agent handles reschedules better. Every test passes. Two days later, callers who ask to cancel are sent into the rescheduling flow. Nothing in the transcript looks broken, so no one notices until the cancellation numbers drop.

Voice agents fail in layers. The speech recognition can be right while the intent is wrong. The intent can be right while the reply comes two seconds late. And a fix in one flow can break another.

This guide sets out the criteria that matter, compares eight platforms against them, and explains where RubricHQ fits.

We build RubricHQ, so we have a stake in this. We’ve tried to keep the comparison fair. Where a competitor is stronger, we say so. Where RubricHQ is behind, we say that too.

What a voice AI testing tool should do

Test with realistic callers. Look for personas with different moods, accents, and background noise, plus callers who interrupt. A tool that only plays polite, scripted callers finds only the failures you already expected.

Run against the deployed agent. The test should use the same call path your customers use. Check which platforms it supports: Vapi, Retell, LiveKit, Pipecat, SIP, or WebRTC.

Score results in a way you can check. Ask how the verdicts are made. Then test the tool yourself. Score 50 real calls by hand and compare the tool’s verdicts with yours.

Help you fix what failed. Finding a failure is only the first step. Ask what happens next: a report, a suggested prompt change, or a fix you approve.

Block bad releases. A good tool runs in your CI pipeline and fails the build when pass rates drop below your threshold. That’s the check that would have caught the dental clinic’s cancel-to-reschedule bug before callers did.

Monitor production. Look for drift alerts and call-level detail. Ask whether latency is shown as an average or as percentiles. Averages hide the slow calls that callers remember. Percentiles such as p90 and p99 show them.

Meet your compliance needs. If you handle health or payment data, ask for the current SOC 2 report and a signed HIPAA BAA, and check where your call data will be stored.

Check the price to start. Some tools have a free tier, and some quote prices only after a demo. Usage-based pricing grows with call volume, so estimate your monthly minutes before you compare. We checked every price in this article in November 2026, so confirm them on each vendor’s site before you budget.

Quick comparison

The platforms, one by one

Hamming

Hamming runs pre-launch testing and 24/7 production monitoring. It supports SIP and WebRTC setups (LiveKit, Daily), multilingual agents including regional Spanish, interruptions, and off-script behaviour.

Price: Quoted after a demo.

Pros

• Shows latency as p50, p90, and p99, so slow calls are visible.
• 24/7 production monitoring with real-time alerts and webhooks.
• Runs tests from the API and in deployment pipelines.
• Tests PCI and HIPAA scenarios and checks PII exposure.
• Dedicated onboarding support, including a Slack channel.

Cons

• Pricing is only available after a demo.
• Its site footer says SOC 2 Type II, but its FAQ says SOC 2 is in progress.

Good fit for teams that want percentile latency and compliance-focused testing.

Coval

Coval is built around simulation volume. It runs large batches of simulated calls in CI, routes conversations to human reviewers, and sends alerts to Slack, email, or a webhook.

Price: Starter is $100 a month, with 100 simulation minutes, 1,000 monitored calls, 5 concurrent simulations, and a 7-day trial that needs a card. Growth is $500 a month, with 1,000 simulation minutes, 10,000 monitored calls, and 25 concurrent simulations. Enterprise is custom.

Pros

• Simulated callers interrupt, hesitate, switch languages, and call from noise, with tool calls in the mix.
• Human review covers smart sampling, one-click overrides, and judge retraining.
• MCP server. Connects to Langfuse, LangSmith, Arize, and Datadog. OpenTelemetry-native, with SIP header tracing.
• Pipecat guide lists built-in latency, interruption, and speech tempo metrics.
• Vendor bake-offs grade agents from different vendors on one scale.

Cons

• Its products page lists GDPR as “in progress,” but its pricing page lists GDPR on every plan. Confirm before you rely on either.
• The Starter plan caps simulation at 100 minutes and 5 concurrent calls.
• We found a Vapi partnership but no Retell integration on its pages.

Good fit for teams that change voice agents often, need a human in the loop, and want large test runs in the pipeline.

Bluejay

Bluejay generates test scenarios from your prompt and customer data. It runs them on a schedule or in CI and monitors production with OpenTelemetry traces. Its Self-Improve feature A/B tests prompt and flow changes against simulated and real conversations, according to Retell’s partner listing.

Price: Pay as you go is $0 plus usage, with a $25 credit. Growth is $500 a month with 1,500 simulation minutes. Scale is $1,000 a month. Bluejay’s public pricing has changed during 2026, so confirm it before you budget.

Pros

• Self-Improve measures each prompt or flow change before it goes out.
• “Digital humans” simulate customers from your data.
• Integrates with Pipecat for simulations and production call evaluation.
• Production monitoring with OpenTelemetry traces and issue clustering.

Cons

• We couldn’t confirm from its public pages whether a person signs off on a change before it goes live. Ask about this in the demo.
• Usage credits add up at higher volumes.

Good fit for teams that want every prompt or flow change measured against simulated and real calls.

Cekura

Cekura focuses on voice. It runs simulations with personas, accents, and interruptions. It red-teams for jailbreaks and PII leaks, and it watches live calls for drift and latency spikes.

Price: Pay as you go is $0 with 300 credits. Voice testing is $0.25 per minute, and monitored calls are $0.05 each. You get 10 concurrent calls, one free seat, and $30 a month for each extra seat. Startup is $500 a month, with about 2,000 test minutes, about 10,000 monitored calls, 50 concurrent calls, and a signed BAA and DPA. Enterprise is custom.

Pros

• Red teaming for jailbreaks and PII leaks.
• Live monitoring for drift, latency spikes, and call drops.
• Signed BAA and DPA on the Startup plan.

Cons

• Built for conversational agents. RAG pipelines and other LLM apps need a second tool.
• Costs rise with call volume.
• Pay-as-you-go logs are kept for 30 days.

Kwindla Kramer, a founder who used Cekura to build Gradient Bang, reviewed it on Product Hunt. He called it a strong testing tool for voice AI apps, including complex features such as subagents.

Good fit for voice-only teams that want red teaming and monitoring in one product.

Roark

Roark starts from production. It replays live calls, turns failed calls into regression tests, and connects to Vapi, Retell, LiveKit, and Pipecat.

Price: Pay as you go is $0 with a $50 credit, at $0.15 per simulated minute. Team is $500 a month, spent as usage, at $0.10 per simulated minute. Enterprise starts at $4,000 a month. These figures come from a third-party read of Roark’s pricing page on October 13, 2026, so check Roark’s site for current prices.

Pros

• Failed calls become regression tests, so each production failure becomes a test.
• Run plans combine flows, personas, and metrics, and can run on a schedule.
• Public pay-as-you-go pricing with a free credit.
• Roark’s YC profile says it processed more than 10 million call minutes in its first six months (2025).

Cons

• Its value depends on call traffic, so it gives less before launch.
• Per-minute and per-metric fees add up.
• One source says its SOC 2 is Type I, while another says Type II.

Good fit for teams already taking live calls who want production failures turned into tests.

Confident AI

Confident AI evaluates voice and text agents in one workflow. Its Voice AI Evals launched in Q3 2026 with seven voice metrics: Voice Naturalness, Speech Intelligibility, Voice Consistency, Turn-Taking Naturalness, Agent Responsiveness, Audio Integrity, and Voice Reliability. They run in the same test as its LLM-judged conversation metrics.

Price: Free is $0, with 2 seats, 1 project, and 5 test runs a week. Starter is $200 a month per organisation. Team is $2,000 a month per organisation. Enterprise is custom. Third-party sites list per-seat prices, which don’t match Confident AI’s own pricing page.

Pros

• Scores audio and conversation in one test run, so voice quality doesn’t need a separate tool.
• Persona-based simulation generates new conversations.
• pytest-based evals run in CI on every pull request.
• Published pricing with a free tier.
• SOC 2 Type II per its site footer. HIPAA BAA on Team and above.

Cons

• Built first as an LLM evaluation platform. Its voice features are newer.
• Live monitoring works on transcripts and traces, not live call audio.

Antonio D., a software architect at a company with more than 1,000 employees, rated it 5 out of 5 on G2 (reviewed July 15, 2026). He praised the fast pace of enterprise feature releases, its red teaming and compliance features, and its Python library, DeepEval.

Good fit for teams that want audio scoring and conversation scoring together, on one platform.

Cyara

Cyara comes from contact centre testing. Botium covers IVR trees, voice bots, and chatbots, and adds regression and load testing. Pulse 360 monitors customer journeys across channels.

Price: Custom, quoted by sales.

Pros

• G2 rates Cyara Platform 4.7 out of 5 from more than 40 reviews (November 2026).
• Built for IVR and contact centre testing at scale.
• SOC 2 Type II attestation, announced in 2021. Ask for the current report.
• AI Trust adds compliance and bias modules.

Cons

• Sales-led pricing with no public tiers.
• Mainly built for large enterprises.

One G2 reviewer, a senior product analyst at a company with more than 1,000 employees, said it stays reliable under high-load tests and that support helps quickly with writing test scripts.

Good fit for enterprises running legacy IVR alongside new AI agents.

Where RubricHQ fits

Most of the platforms above can run a test call. The difference we care about is what happens after a call fails.

Opportunities groups recurring mistakes across an agent’s conversations. Each card shows the failure type, the stage where it happens, its severity, the count over the last 30 days, evidence calls with transcript excerpts, what goes wrong, and what the agent should do instead.

Prompt Optimizer takes up to five calls, usually the failed ones. It lists the gaps behind the failures and ties each gap to the metric that failed. You can edit, remove, or add gaps. It then proposes a rewrite and shows a word-level diff with the score change. You review the changes before anything is applied, and you can go back to any earlier version. Pushing the change to your live agent is a second step, and RubricHQ supports Vapi and Retell for that.

Flow shows calls moving between the stages you define, and where they leave. Click a stage to see the calls behind it, and filter them by passed or failed. Flow also shows ideal paths, where a call reaches its outcome and passes at least 80% of the time, and problem paths.

Simulation starts from your prompt. Paste it in, and the AI generates scenarios. Simulated calls run through Vapi, Retell, LiveKit, or Pipecat, over phone, web, or text, in 65+ languages. Personas cover mood, accent, adversarial callers, and a probe that tries to extract personal data. You can also simulate poor network conditions. Golden call replay lets you save the calls that must always pass and rerun them before any change goes out.

Where we are behind. SOC 2 and HIPAA are still in progress.

Starting costs nothing. You get 200 credits with no card needed, valid for 14 days. The Growth plan is $399 a month for 12,000 credits and up to 50 members. It adds the Optimizer, Co-Pilot, Flow with ideal and problem paths, alert monitors, scheduled runs, and SSO.

How to pick one in a week

Shortlist two tools that fit your stack and your compliance needs. Run both against the same set of your own failed calls, including the ones that hurt most. Then hand-score 50 of those calls and compare each tool’s verdicts with yours. The tool whose verdicts match yours, and whose output tells you what to change, is the one to trial.

FAQ

Is there one best tool? No. The right tool depends on whether your main gap is simulation volume, compliance, live call replay, or fixing prompts.

Can I test a Vapi or Retell agent without rebuilding it? Most tools in this list connect to a deployed agent. RubricHQ supports Vapi, Retell, LiveKit, and Pipecat. Hamming, Cekura, Coval, Bluejay, and Roark also list Vapi or Retell integrations.

Are there legal rules for voice calls? For outbound calls in the US, the FCC’s 2024 ruling treats AI-generated voices as artificial under existing consent rules. Test disclosure and opt-out handling, not only whether the task got done.

Try RubricHQ free. Start with 200 credits, no card needed. For a walkthrough or questions, email [email protected].