News & Insights

Compare the top voice agent testing platforms in 2025. Detailed feature matrix, pricing, and recommendations based on Hamming's analysis of 1M+ calls across 50+ deployments.

Explore how logging, storage, and retention shape the reliability and compliance of voice agents, and understand the architectural choices behind routing, observability, and regulatory alignment.

Financial voice agents sit on regulated data and core banking workflows—explore why authentication, PCI handling, tool calls, and model drift need to be validated under real conditions before deployment.

Learn about automated testing for healthcare voice agents: validate safety, HIPAA alignment, clinical accuracy, escalation triggers, and peak-load performance with Hamming.

Extracted from our podcast The Voice Loop, this episode recap explores why Ultravox moved from cascaded pipelines to speech-to-speech models. Learn how GLM 4.6, audio-native training, and Voice Agent Bench shift the trade-offs in latency, reasoning, and real-world performance.

Explore how to test voice agents built with LiveKit.

Explore three ways to test voice agents built with Vapi.

Explore three ways to test voice agents built with Retell.

Explore seven real-world ASR failure modes teams see in production voice agents, plus how to test and monitor for these failure modes to build and deploy reliable voice agents.

A practical guide to ASR/STT and TTS in voice agents - covering accuracy, latency, prosody, testing, and production monitoring.

Learn how Hamming helps healthcare teams ensure HIPAA-compliant voice agents through scenario-based testing, compliance validation, and continuous QA.

We're proud to announce that Hamming has successfully completed our SOC 2 audit and is now SOC 2 compliant.

Extracted from our podcast The Voice Loop, this episode recap explores why voice agents continue to break at scale despite advances in STT, TTS, and LLMs. Learn how organizational processes, vendor chains, and operational infrastructure shape voice agent reliability

Extracted from our podcast The Voice Loop, this episode recap explores how input audio quality is one of the biggest bottlenecks in voice AI. Learn how degradation across devices, environments, and transmission layers impacts ASR accuracy.

Explore the five failure modes that undermine clinical voice agents. Learn how perception stability, guardrail enforcement, multi-agent reasoning, workflow sequencing, and latency shape real clinical reliability—and why testing the full pipeline is essential for safe healthcare deployments

Explore why accuracy is only one dimension of conversational AI performance. Learn how audio stability, ASR behavior, retrieval alignment, and multi-turn reasoning shape real reliability and why evaluating the full pipeline is essential for production-ready voice agents.

Extracted from our podcast The Voice Loop, this episode recap explores how Voice AI teams are moving beyond synthetic benchmarks to real reliability—covering demos, ASR bottlenecks, and the future of production-ready voice QA.

Learn how to use AI voice agent analytics to improve CSAT. Discover how Hamming's observability platform helps enterprises measure latency, model accuracy, and user reactions to turn customer satisfaction into a real-time operational signal.

Voice agent reliability is the defining measure of quality for production voice AI. Learn best practices including instrumentation, version control, regression testing, failure handling, and continuous monitoring to build reliable voice agents.

Learn how to implement effective regression testing for AI voice agents using Hamming's Regression Detection Framework. Prevent performance degradation and ensure consistent quality across updates with automated behavioral drift detection.

Learn how to design and optimize voice user experience (VUX) for AI voice agents. Discover best practices for creating intuitive, engaging, and effective voice interactions.

Learn how to measure and improve voice agent performance with key metrics like latency, accuracy, prompt adherence, escalation rates, and goal completion. Discover common challenges and how Hamming provides the right infrastructure with testing, monitoring, dashboards, and feedback loops.

Learn how voice agent guardrails protect your AI systems from risks like prompt injections and compliance violations. Discover how testing and monitoring ensure production-ready voice agents.

Most prompts fail once they hit production. Learn how to design modular, testable, and reliable prompts that don't break in production.

Voice AI poses serious compliance risks, from HIPAA violations to PCI DSS failures. Discover how to keep voice AI agents secure and compliant. Test against key regulatory framework including HIPAA and PCI DSS risks and monitor every call in real time.

Multi-step voice agents introduce cascading failures, context loss, and latency challenges. Learn why traditional testing falls short and how end-to-end voice observability ensures reliable production conversations.

We jailbroke Grok’s AI companion Ani using prompt injection testing, exposing latency, QA, and guardrail failures. Here’s why observability matters.

Optimizing latency is challenging if you don't actively monitor it. Learn how to track the key latency metrics in order to optimize latency effectively.

Learn how to evaluate AI voice agent performance in production with Hamming. Track accuracy, latency, reliability, and end-to-end observability to ensure agents deliver consistent and reliable conversations.

Voice observability is the missing discipline in Conversational AI. Learn what it means to define voice observability, what to measure and how to measure each layer of the stack.

State transitions are the most critical failure points in multi-agent voice systems. This guide covers the mechanics of handoffs between agents, common breaking points, and practical strategies for designing, testing, and monitoring reliable transitions.

Proactively monitor your AI voice agents in production with Hamming's always-on Heartbeats. Catch silent failures, reduce QA overhead, and get alerted instantly when critical conversation paths break.

Discover how to build analytics dashboards designed for AI voice agents, with insights into KPIs that matter, real-time monitoring, and avoiding common pitfalls when measuring LLM performance.

Legacy tools fail at understanding AI voice agents. Learn how modern analytics offer real-time insights, improve accuracy, and surface blind spots.

Scripted voice tests pass in the lab but fail in production. Compare Hamming's stress-testing and live observability with Vapi and Retell's happy-path suites, then learn how to harden your agent.

The best voice AI teams—from healthcare systems to global enterprises—choose Hamming because it's the only complete platform covering the entire QA lifecycle. Here's what they look for and why Hamming delivers.

We're excited to announce our $3.8M seed round led by Mischief, with participation from YCombinator, AI Grant, Pioneer, Coalition Operators, Coughdrop, and notable angels.

Automate DTMF testing with Hamming AI's new feature. Simulate keypad inputs, test menu navigation, and validate voice agent responses to DTMF tones in your automated test scenarios.

New feature enables teams to re-run selected scenarios from existing datasets, streamlining the testing process for voice AI agents with targeted testing.

New debugging features provide clear insights into call termination and SIP status, helping teams quickly identify and resolve voice AI agent issues.

Fluents.ai customers now get access to Hamming AI's comprehensive voice agent testing suite, while Hamming AI customers receive 15% off Fluents.ai's enterprise-grade AI Voice Agents workflows.

New analytics module provides comprehensive performance visualization for AI voice agent testing, including latency metrics, call durations, and LLM-based evaluations.

Access real-time emotional characteristics monitoring in production calls with Hume AI integration. Monitor pitch, tone, and rhythm to gauge caller sentiments during voice agent interactions.

A brief note of thanks from our team as we continue building better voice AI testing solutions.

Reflecting on an energizing weekend at AI Grant Demo Day and doubling down on our mission to make voice AI testing more robust and accessible.

Learn how Lilac Labs automates drive-thru order testing to ensure accuracy and handle complex scenarios like dietary restrictions and allergies.

Hamming AI and Retell AI announce strategic partnership to provide real-time monitoring and automated testing for AI voice agents, offering immediate alerts for agent mistakes and hallucinations.

We bet your LLM can find a bug in a snippet of code. But how about 25 pages of code? We propose a new 'needle in a haystack' analysis called 'Bug in the Code Stack' that tests how well LLMs can find bugs in large codebases.