Blog

An enterprise voice AI procurement checklist: the stakeholders and gates — from need and RFP to security, legal, and rollout — so nothing is skipped.

A voice AI RFP checklist that forces evidence, not marketing: accuracy on your data, latency percentiles, security, SLAs, pricing, and evaluation method.

A playbook for a voice agent bake-off: set pass/fail criteria first, give every vendor identical conditions, run long enough, and decide on the results.

Public voice AI leaderboards don't predict your production. Why to benchmark voice agents on your own call data, and build one that fits your traffic.

The only fair way to compare voice agents is one shared test set run identically against each. How to build it from your real calls and reuse it over time.

How to benchmark voice agent vendors fairly: representative data, fixed definitions, controlled conditions, and a sample large enough to be reproducible.

Vendor-reported voice AI metrics are self-measured on cherry-picked data with private definitions. Why they don't compare — and what to measure instead.

How to evaluate voice agent vendors: score each on accuracy, latency, task success, safety, and cost using your own test calls, not their numbers.

A pre-launch voice agent testing checklist: speech accuracy, latency, turn-taking, task success, escalation, safety, and load — verify before you go live.