Hamming AI Blog

7 Non-Negotiables for Voice Agent Quality Assurance Software

Discover the seven core capabilities every voice agent QA platform must deliver—from end-to-end audio and chat testing to regression detection, load simulation, and multilingual validation. Learn how Hamming helps teams maintain voice agent reliability through continuous testing, traceability, and real-time observability.

How to Use AI Voice Agent Analytics to Improve CSAT

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.

How to Monitor Voice Agent Outages in Real Time

Voice agent outages often go undetected until users complain. Learn how to monitor ASR, NLU, and TTS layers in real time with synthetic calls, automated alerts, and the right monitoring signals to catch failures before customers notice.

Best Practices to Improve AI Voice Agent Reliability

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.

AI Voice Agent Regression Testing

Learn how to implement effective regression testing for AI voice agents to prevent performance degradation and ensure consistent quality across updates.

Top Voice AI Testing Tools

Discover the best voice AI testing tools for ensuring quality, reliability, and performance of AI systems. Compare features, capabilities, and use cases.

Voice User Experience

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.

Voice Agent Performance

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.

An Introduction to Voice Agent Guardrails

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.

How to Write Voice Agent Prompts That Don't Break in Production

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

AI Voice Agent Compliance & Security

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.

Testing Multi-Step Voice Agents: Why End-to-End Observability Changes Everything

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

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

Why Hamming AI Is the Best Voice Agent Evaluation Platform

Hamming AI sets the industry standard for evaluating AI voice agents. Discover how its unique approach, deep observability, and real-time metrics help teams build reliable and production-ready voice experiences.

How to Optimize Latency in Voice Agents

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.

How to Evaluate AI Voice Agents Performance in Production with Hamming

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: The Missing Discipline in Conversational AI

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.

Why State Transitions Matter in Multi-Agent Voice Systems

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.

An Intro to Production Monitoring for Voice Agents

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.

Guide to Choosing the Right Voice Agent Stack

A comprehensive framework for selecting and integrating voice agent components for production, covering architecture patterns, platform comparisons, and a 4-layer quality framework with a 30-day implementation plan.

The Anatomy of a Perfect Voice Agent Analytics Dashboard

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.

A Guide to Quality Assurance for AI Voice Agents

Learn how to implement AI voice agent quality assurance with proven strategies for voice agent testing. Discover the 4-layer framework for ensuring AI voice agent QA across infrastructure, execution, user satisfaction, and business outcomes.

Voice Agent Analytics: Why Legacy Analytics Solutions Don't Work Anymore

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

Hamming vs. Retell & Vapi QA Testing: Why platform QA isn't enough

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.

Hamming AI Raises $3.8M Seed Round

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.

DTMF Support for Comprehensive Voice Agent Testing

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.

Selective Scenario Re-runs for Voice AI Testing

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

Enhanced Call Debugging with SIP Status Tracking

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

Hamming AI Partners with Fluents.ai for Enhanced Voice AI Testing

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.

Hamming AI Launches Advanced Call Analytics for Voice Agent Testing

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

Hamming AI Integrates with Hume AI for Enhanced Voice Agent Monitoring

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.

Thanksgiving Update from Hamming AI

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

Multi-Language Support for Voice AI Testing

Test your AI Voice Agents in 11 languages including Dutch, English, French, German, Hindi, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish. Ensure reliable voice interactions across global markets.

AI Grant Demo Day: A Weekend of Learning and Connection

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.

Customer Spotlight: How Lilac Labs (YC S24) Ensures Drive-Thru Order Accuracy with Hamming AI

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

Hamming AI Partners with Retell AI for Enhanced Voice Agent Testing

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.

Can LLMs find bugs in large codebases?

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.