Posts tagged with "Conversational Ai"

Learn how Cekura's red-teaming framework tests chat and voice AI agents for bias, toxicity, and jailbreak vulnerabilities before they reach production.

Most voice AI failures don't happen because of hallucinations or mispronunciations. They happen during silence. Learn how to engineer resilient voice AI systems that handle the milliseconds between words.

Discover why Cekura provides superior monitoring capabilities compared to traditional tracing platforms for conversational AI agents.

How to monitor AI chat and voice agents in production using Cekura’s quality metrics, dashboards, and smart alerting.

Learn why single-turn evaluation methods are insufficient for conversational AI and how multi-turn simulations provide a more accurate assessment of chatbot performance, context awareness, and conversation quality.

Explore 12 key metrics—like interruptions, WPM, sentiment, and talk ratio—to enhance your AI conversation monitoring and insights.

Discover the 6 most important metrics for monitoring AI conversations—Instruction Following, Latency, Hallucination Rate, CSAT, Interruption Handling, and Voice Clarity—to ensure reliable, high-performing voice and chat agents.

Should you switch to GPT-5, Gemini 2.5, or DeepSeek for your Voice AI or Chat AI agents? Learn from real A/B testing, benchmarking, and regression testing insights on choosing the right LLM for Conversational AI.

Learn how silent errors in LLM-powered systems can erode performance and trust plus practical tips to catch failures early and keep your AI reliable.

Explore top TTS models that deliver authentic voices. Learn how human-like speech improves conversational AI experience and what to test in your next voice agent."

Cekura secures $2.4M in funding to power reliable QA for voice and chat AI agents—bringing AI testing and observability to the next generation of Conversational AI Agents

Explore how Cisco and Cekura are delivering seamless end-to-end AI Testing, observability for enterprise conversational AI deployments.

Dive into emerging trends and real-world applications in conversational AI: from voice AI agents in healthcare, finance, logistics and other sectors

Discover red teaming strategies that expose vulnerabilities in your Voice AI and Chat AI agents before they scale. Learn how adversarial AI testing helps create safer, more LLM agents

First call resolution measures issues closed without a callback. Get the FCR formula, 2026 benchmarks by industry, and 7 ways to raise it on AI calls.

See 7 voicebot in banking use cases, from card locks to fraud alerts, plus the account-number accuracy bar and the Reg E and TCPA duties your tests must cover.

Voicebot vs chatbot compared on response time, speech recognition error, cost, and TCPA exposure. Learn the key differences and when to use each in 2026.

Dialogflow CX pricing for 2026: Flows and Playbooks rates, trial credits, voice billing rules, hidden costs, and a 20,000-call monthly cost model to copy.

What is NiCE CXone? See how the cloud contact center platform routes calls, runs AI agents, and bundles WFM and analytics, plus pricing, pros, and cons.

Amazon Lex pricing guide for 2026. Compare text, speech, and streaming rates, free tier rules, and what a real voice or chat agent costs you each month.

Conversational AI in banking, covering six servicing use cases, the benefits with real numbers, the rules that apply in 2026, and how to verify any of it.

Conversational AI in insurance: 9 use cases across FNOL, claims, and servicing, the rules each call triggers, and how to test agents before they dial.

Sierra AI pricing is outcome-based with no published rate. See what sets the invoice, how the blended model works, and how to model cost before a sales call.

AI red teaming in 2026: seven attack methods, the tools that run them, the OWASP and EU AI Act duties behind them, and a 1-to-5 scoring rubric to copy.

Containment rate measures the sessions your AI agent closes without a human. Get the formula, 2026 benchmarks, measurement traps, & 7 ways to raise it.

Decagon AI competitors compared for 2026 on billing shape, voice maturity, and verified pricing, plus why published resolution rates don't compare.

Sierra AI alternatives compared for 2026 on voice maturity, deployment model, and real pricing, plus the pre-launch testing each one still needs.

Sierra AI vs Decagon: how each builds CX agents, what outcome-based pricing leaves undefined, and where QA fits. Get the four-axis scorecard before you sign.

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

Compare the 7 top conversational AI platforms with voice CRM in 2026, ranked by how deeply each one reads and writes your records live during the call.

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

Conversational voice AI lets software hold a real-time spoken conversation. Here is how the conversation loop works and the key platforms to know in 2026.

Chatbot evaluation goes beyond pass/fail. Learn the 3 methods and 8 metrics engineering teams use to catch failures before production.

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.

I tested the top conversational AI testing tools and documented what works. Best practices, honest reviews, and updated pricing, all in one place for 2026.

Tired of missed calls? We tested 15+ AI answering services so you don't have to. Here are the 7 best options for 2026, ranked by real call performance.

Master chatbot testing for LLM-powered agents with this 2026 guide. Learn testing strategies, checklists, and tools to build reliable bots.

This ElevenLabs review for Conversational AI compiles what real users say about voice quality, pricing, and the gaps no one talks about. Here's what to know for 2026.

Cekura is the CI/CD testing framework for conversational agents with GitHub and Jenkins. Automatically run multi-turn conversation tests, gate PRs, catch regressions, and ship reliable AI agents with confidence using Cekura.

End-to-end conversational AI testing with full CI/CD integration. Validate flows, models, and voice/chat agents with automated regression, load, and accuracy checks with Cekura

Evaluate your conversational AI agents for accuracy, safety, consistency, and robustness using Cekura’s full reliability testing suite.

Cekura provides unified testing for IVR and chatbot systems, ensuring reliable cross channel flows, edge case coverage, and real world performance at scale.

Cekura’s dashboards centralize chat and voice agent test results with real-time metrics, alerts, and regression tracking for better QA insight.

Cekura provides a complete conversational AI testing suite that automates simulation, regression, and live monitoring for chat and voice agents. Test accuracy, latency, safety, and compliance at scale.

Cekura is the leading AI chatbot testing platform. Automate scenario generation, regression testing, and production monitoring to build reliable, compliant, and scalable conversational agents.

Automated AI agent evaluation with Cekura. Test, monitor, and improve voice and chat agents using scenario simulation, metrics, observability, and regression testing.