Decagon vs Yellow.ai

A/B-testing suite for AI support agents: structured experiments (tone, logic, flows) against live traffic with control groups, statistical-significance testing and gradual rollout.

Dashboards and natural-language querying ('Ask AI') over support data: CSAT/deflection performance tracking, heatmaps, customer-journey visualization and knowledge-base performance.

Analyzes support conversations to detect gaps in a company's help center and auto-generates draft articles, ranked by impact, with monthly updates.

Integrated testing suite (internally called 'Simulations') that validates AI-agent behavior across channels before production deployment.

Always-on monitoring and QA for AI and human agent interactions against custom quality criteria.

Builds and runs customer-support agents that resolve enquiries over chat, email and voice.

Decagon's chat channel — an AI agent that handles live customer conversations in a web or in-app chat surface.

Decagon's email channel — agents that read and answer customer email threads rather than routing them to a queue.

Decagon's voice channel — an AI agent that answers customer phone calls in place of a hold queue.

Decagon's authoring layer for the rules an AI support agent follows, so non-engineering teams can build, iterate on and scale agents.

An AI partner built into Decagon that helps teams build and improve support agents — distilling best practices from hundreds of Decagon deployments into guidance for the builder, and auto-tuning the agent via "Duet Autopilot," which improves it with every conversation it handles.

AI suggestions and workflows for human support teams handling live conversations.

Build enterprise customer-service AI agents from natural-language prompts.

Conversation analytics over AI agent interactions, with visibility into customer behaviour and agent performance.

Retrieves enterprise knowledge for conversational agents using agentic RAG.

Uses LLMs to understand unstructured support emails, infer intent and urgency, and trigger automated resolution or escalation workflows.

Enterprise voice AI platform running voice agents with cloned, human-sounding voices.

Customer- and employee-facing agents built without code: an agent builder across channels, a knowledge base the company calls agentic RAG, a copilot for previewing and debugging what an agent did, automated testing before release, and Nexus Vox for voice.