Posts tagged with "Voice Agent Testing"

Run AI agent testing inside CI/CD: version test suites as code, validate free with dry runs, and gate every merge with GitHub Actions. See how Cekura does it.

How to optimize voice AI agent cost and performance together, with measured per-turn latency, pass rates, and the real price of bounding your worst case.

Closing the eval loop was the algorithm. Here's the product and the POC playbook that made customers willing to run it on their own production voice agents.

Learn the mechanics of endpointing and turn detection in voice AI, the three signals modern agents use, and how to measure and test conversational timing at scale.

Cekura has an MCP server. Coding agents (Claude Code, OpenAI Codex, Cursor, Windsurf) can trigger voice agent test runs, schedule recurring evals, and review pass/fail results without leaving their editor.

Learn how to build a self-improving voice agent loop that automatically diagnoses failing evals, applies prompt fixes, catches regressions, and iterates to 100% pass rate.

Developer's guide to voice AI evaluation in 2026. Metrics, scenario testing, hallucination detection, persona QA, and per-stack testing for major voice stacks.

Cyara Botium bot testing reviewed: what G2 reviewers praise, the learning curve and pricing complaints, and the LLM voice metrics the reviews never cover.

How voicemail detection works in voice AI: the three detection methods, the beep problem, the FCC two-second rule, and how to test every branch before you dial.

AI voice bot accuracy rates split into four layers. Real 2026 benchmarks for transcription, intent, task success, and orchestration, plus how to test yours.

LiveKit vs Vapi compared on infrastructure ownership, true per-minute cost, concurrency ceilings and compliance pricing, plus where a QA layer belongs.

Voice AI sentiment analysis for upsell offers fails on timing. Compare four trigger designs, real accuracy ceilings, and the tests that catch a bad offer.

AI voice technology is the pipeline behind spoken AI agents. This guide covers how it works, where each layer fails, and what that costs in production.

Conversational AI voice bots skip the menu and carry the full conversation. This covers the architecture, where they break, and which platforms hold up.

Cyara pricing is tailored to each product. This breakdown covers what each one does, who it makes sense for, and five alternatives with published pricing.

How to test voice AI agents using 7 methods, from scripted calls to red teaming, plus what each catches, what it misses, and the right order to run them.

LiveKit Agents is an open-source framework for realtime voice AI. Here is how the SDK works, how to build an agent, and what to test before launch.

Speaker diarization tells you who spoke when. Learn how it works, why DER benchmarks mislead, where it fails on agent calls, and how to test in production.

Voice activity detection decides when your agent hears speech. A developer's guide to VAD models, threshold tuning, the four failure modes, and testing.

Most teams answer 'what is an AI voice agent?' too late. This guide covers how the pipeline works and where deployments break in production.

Cyara omnichannel CX testing gets high marks from enterprise QA teams. The licensing structure and agentic limitations tell a more complicated story.

Retell AI voice automation features in 2026, broken down across building, voice, telephony, monitoring, and pricing, and the limits that shape deployments.

I tested Twilio vs Vapi across deployment, billing, and production QA — one comparison turned into three tools solving three different problems.

Vapi vs ElevenLabs solve different jobs, and neither tests itself. Here are the key differences in 2026, plus where a QA layer fits in your voice stack.

Best practices for AI voice agent testing, with honest tradeoffs: 8 rules that catch the failures real callers trigger before they reach production.

Learn how to test your voice agent after building it, across six stages from component checks to production monitoring, with a clear pass bar for each.

AI voice agent ROI calculator guide to find out how much your team can save by automating calls, with benchmarks and a step-by-step model for 2026.

Hallucination detection for voice AI measures whether a voice agent's spoken answers stay grounded in its knowledge base instead of inventing facts. Here is how RAG grounding checks, factuality evals, and Cekura catch hallucinations before production.

Instruction following evaluation tests whether a voice bot obeys its system prompt across a full call. How Cekura scores instruction adherence at scale.

Outbound voice AI QA is the practice of simulating, scoring, and load-testing an outbound voice agent before it runs a live calling campaign. This guide covers what to test, how to test outbound voice agents at scale, the compliance checks that matter, and where Cekura fits.

Persona-based voice AI QA tests whether a voice agent stays accurate, consistent, and on-brand across many simulated caller personas. Here is how it works, why it matters in 2026, and how Cekura runs it at scale.

Compare the 9 best AI virtual receptionist voice technology tools in 2026 across workflow testing, infrastructure behavior, production monitoring, and risk.

Voice AI fails when humans push it past training data. Here's how AI voice assistants process language across 4 layers and where each breaks.

LLM as a judge uses a large language model to score AI outputs at scale. Learn how it works, its pros, cons, and best practices for voice and chat agents.

Learn how voice quality testing works, the methods and tools teams use, and how to test speech clarity, latency, audio quality, and real call performance.

Learn how to do a penetration test for voice AI agents across prompts, audio, tool calls, PII leaks, and regression checks before launch. Here are 8 steps.

Most teams pricing AI voice agents are guessing. Here's the 6-model breakdown with real platform costs and examples you can use today.

Voice agent performance testing goes beyond transcripts. This guide covers five methods that catch what manual reviews miss, with examples from real teams.