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Automated Testing & Call Review for your AI Voice Agent

Elixir ensures your voice agent is reliable and works as expected in production.
Simulate realistic test calls. Automatically analyze conversations and identify mistakes. Debug issues with audio snippets, call transcripts, and LLM traces all in one platform.

Our visionary partners
AriseHealth logoToogether logoEphicient logo2020INC logo

The AI Ops & QA platform built for multimodal, audio-first experiences

Start monitoring instantly...

MONITORING & ANALYTICS

Track call metrics & identify mistakes at scale

Measure agent performance – interruptions, transcription errors, tool calls, user frustrations and more out of the box metrics

Find patterns between agent mistakes and user behavior

Detect anomalies in real time and receive Slack notifications for critical concerns

TRACING

Debug issues quickly with the help of audio snippets, LLM traces, and transcripts

Detailed traces for complex abstractions: RAG, Tools, Chains & more

Play back audio snippets to hear user <> agent dialog and identify performance bottlenecks

Listen to focused call sections to speed up review

SCORE & REVIEW

Streamline your manual review process with call auto-grading

Define use-case specific success metrics & scoring rubric for your conversational system

Automatically triage "bad" conversations to a manual review queue 

Provide human-in-the-loop feedback to improve auto-scoring accuracy

TESTING & SIMULATION

Simulate 1000s of calls to your agent for full test coverage

Configure language, accent, pauses, tone to test agent on realistic cases

No more manual testing. Run auto-tests every time you make a significant change

Train testing agent on real conversation data to mimic users

MONITORING & ANALYTICS

Track core metrics & identify mistakes at scale

Measure agent performance – interruptions, transcription errors, tool calls, user frustrations and more out of the box metrics

Find patterns between agent mistakes and user behavior

Set thresholds and receive Slack alerts for critical concerns

TRACING

Debug issues quickly with the help of audio snippets, LLM traces, and transcripts

Detailed traces for complex abstractions: RAG, Tools, Chains & more

Play back audio snippets to hear user <> agent dialog and identify performance bottlenecks

Listen to focused call sections to speed up review

SCORE & REVIEW

Streamline your manual review process with call auto-grading

Define use-case specific success metrics & scoring rubric for your conversational system

Automatically triage "bad" conversations to a manual review queue 

Provide human-in-the-loop feedback to improve auto-scoring accuracy

DATASET

Test your agent on a comprehensive dataset of scenarios

Save edge cases that came up in real conversations

Simulate new prompt iterations on your datasets before deploying

Use datasets for fine tuning, few shot, or prompt improvements

MONITORING & ANALYTICS

Track core metrics & identify mistakes at scale

Measure agent performance – interruptions, transcription errors, tool calls, user frustrations and more out of the box metrics

Find patterns between agent mistakes and user behavior

Set thresholds and receive Slack alerts for critical concerns

TRACING

Debug issues quickly with the help of audio snippets, LLM traces, and transcripts

Detailed traces for complex abstractions: RAG, Tools, Chains & more

Play back audio snippets to hear user <> agent dialog and identify performance bottlenecks

Listen to focused call sections to speed up review

SCORE & REVIEW

Streamline your manual review process with call auto-grading

Define use-case specific success metrics & scoring rubric for your conversational system

Automatically triage "bad" conversations to a manual review queue 

Provide human-in-the-loop feedback to improve auto-scoring accuracy

DATASET

Test your agent on a comprehensive dataset of scenarios

Save edge cases that came up in real conversations

Simulate new prompt iterations on your datasets before deploying

Use datasets for fine tuning, few shot, or prompt improvements

TESTING & SIMULATION

Simulate 1000s of calls to your agent for full test coverage

No more manual testing. Run auto-tests every time you make a significant change.

TESTIMONIALS

Elixir is the only LLM observability product on the market we've found that works well for voice first products.

Josh Singer

Co-founder, Eigen

The Elixir team has been an incredible thought partner in helping us navigate how to build a reliable voice agent.

Ralph Ma

CTO, Maia

Elixir is truly at the cutting edge of voice AI. They understand all the challenges with building and monitoring voice agents.

Sean O'Bannon

CTO, ReMatter
INTEGRATIONS

Compatible with your AI stack

LLM Providers
Vector DBs
Frameworks
Telephony & WebRTC
Transcription & Voice
LLM Providers
Vector DBs
Frameworks
Telephony & WebRTC
Transcription & Voice