Datadog for Voice AI

The Observability + Testing layer Every Voice Agent Needs

From simulation to production monitoring — Tuner gives you full visibility at every stage. Catch failures before you ship, and before your users find them.

Monitor Your First 100 Calls Free, No Credit Card Required

A Fortune 500 company shut down their voice AI after $300M.

A Fortune 500 company shut down their voice AI after $300M.

They didn’t have Tuner.

They didn’t have Tuner.

See every failure as it happens

Catch issues before your customers do

Fix fast, ship with confidence

Voice-native observability. Not adapted from text.

Observe

Understand Exactly What’s Happening in Every Call

See every intent, response, and outcome structured and searchable. Know what users asked, where the agent fumbled, and why, without listening to calls or digging through raw transcripts.

Monitor

Catch Problems Before Your Users Do

Set your own definition of failure: missed intents, hallucinations, broken tool calls, cost spikes. Tuner watches every live call and alerts you the moment something breaks your rules.

Analyze

One Dashboard for Your Entire Voice Operation

Every agent, every call, every trend in one place. Stop context-switching between logs, spreadsheets, and gut feel. See what’s working and what isn’t, across your whole system.

Simulate

Stop Calling Your Own Voice Agent. Simulate It.

Tuner runs real voice calls via AI callers — personas, accents, routine vs. pressure scenarios — built for your own use case. Uses the same production Evals and guardrails with no extra setup, so you catch failures before they reach live callers.

Improve

Know the Impact of Every Change You Ship

Prompt tweak, model swap, config update. Tuner tells you exactly what moved and why. Catch regressions before they reach users and validate wins with real production data.

Simulation + Production Visibility. Two Lines of Code.

The same integration runs AI caller simulations and live monitoring. No infrastructure changes. No lengthy setup. Connect your agent and start seeing real data in under 5 minutes.

1

Connect Your Agent

Add two lines of code or use a no-code connector. Works with Retell, Vapi, and custom stacks out of the box.

2

Define What to Monitor

Choose from 30+ predefined metrics or let MCP auto-configure everything based on your agent setup.

3

Run Call Simulation

Launch AI callers with realistic personas and scenarios through the same hooks.

4

Go Live with Confidence

Real-time alerts and dashboards from your very first call. No warming-up period, no manual tuning.

Python, LiveKit
from tuner import TunerPlugin

async def entrypoint(ctx: JobContext):
    session = AgentSession(...)
    TunerPlugin(session, ctx)
    await session.start(...)

Set Up in Minutes with MCP

Set Up in Minutes with MCP

Connect Tuner’s MCP to your IDE or chat app and skip the manual setup entirely. Works with Cursor, Claude, and any MCP-compatible environment.

Connect Tuner’s MCP to your IDE or chat app and skip the manual setup entirely. Works with Cursor, Claude, and any MCP-compatible environment.

01

Reads Your Code, Prompts and README

Tuner reads your existing files to understand exactly what your agent is built to do. No forms, no onboarding calls, no guesswork.

02

Auto-Recommends Your Configuration

Tuner suggests the right setup instantly, choosing from 30+ predefined metrics or proposing custom evaluations tailored to your specific agent.

03

Edit Anytime From Your IDE

Add evals, adjust thresholds, update monitoring logic without ever leaving your development environment. Your config lives where your code does.

Know the Moment Something Breaks

Get notified the moment your agent hallucinates, misses an intent, or costs spike, wherever your team lives.

ALERT DESTINATIONS

Slack

Email

PagerDuty (soon)

Webhooks (soon)

Stress-Test Your Agent. Before Real Callers Do.

With your evals configured, Tuner’s AI Callers place real voice calls to your agent — scored against the same Evals, Call Outcomes, and Intents already running in production.

ROUTINE

Happy Path Testing

AI callers simulate your everyday customers — cooperative, on-topic, working through normal workflows.

PRESSURE

Find the Breaking Point

Unhappy customers, edge cases, people trying to bypass your process. If your agent has a breaking point, this finds it.

EDGE CASE

Control Your Scope

Test your entire use case or narrow it to a specific Intent or Call Outcome.

Simulation calls

Explore Call Simulation

Ship. Learn. Improve. Repeat.

Every call teaches you something. Tuner structures what you learn, surfacing exactly what failed, why it failed, and how to fix it. Then run simulations to validate your fix before it reaches production, so each deploy is better than the last.

01

Define & Simulate

Set intents, outcomes, and checks. Use simulations to exercise those definitions on every iteration.

02

Observe

Every call classified automatically. Patterns surface without you having to look.

03

03

Analyze

See exactly which intents fail, what drifted, and what changed between versions.

04

04

Improve

Tuner tells you what to fix. Act on evidence, ship the change, and validate it worked.

Try our Free evaluation framework builder

Get a tailored evaluation structure for your industry in seconds. No sign-up needed.

One Platform. Every Stakeholder Covered.

From debugging a failed call to proving ROI to the board, Tuner gives every role on your team exactly what they need, from the same source of truth.

Debug Faster. Ship Changes With Evidence.

What Tuner gives you
  • Full call traces: LLM, TTS, STT, tool calls
  • Tool call breakdown: status, failure, delay per API call
  • Alerts the moment a pattern breaks
  • Run hundreds of simulated calls before every deploy
What you act on
  • Hallucinations and silent API errors
  • Latency spikes and provider timeouts
  • Regressions after every prompt or config change

Enterprise-grade security

GDPR compliant. SOC 2 in progress. Your transcripts, evaluations, and metadata handled with production-grade controls.

Privacy policy

Frequently asked questions

What is Tuner?

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What is voice AI analytics?

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What’s the difference between analytics and observability?

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When does Tuner make sense to use?

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How long does setup take?

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Which voice platforms does Tuner support?

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Who is Tuner built for? Do I need to be an engineer to use it?

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Does Tuner support alerts and monitoring?

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Can I define my own evaluations and metrics?

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How is Tuner priced?

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Is my call data private and secure?

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