Voice AI fails in production for predictable reasons. We built a method that surfaces those reasons before they cost you a rollout. Five phases. Each one with defined deliverables, each producing artifacts your team owns after we leave.
Vendors define success as "the call completed." Operations defines success as "the customer didn’t escalate, didn’t churn, and didn’t tie up a human agent for cleanup."
Before any technology decision, we calibrate on what "working" actually means for your contact center. Most failed voice AI rollouts can be traced back to the absence of this phase.
In Calibration, we run structured interviews with operations, IT, compliance, and CX leadership. We map your current call taxonomy: what calls happen, how often, how they resolve, what they cost. We identify the 3-5 call types where voice AI has the highest probability of success and the lowest probability of catastrophic failure.
A ProofNorth eval suite is not a list of test calls. It is a structured evaluation harness that measures performance under load, in production, continuously.
Before we build or buy anything, we design the test that proves it works. This is the phase that almost no consultancy and almost no vendor does well. We design the eval suite first, then evaluate vendors and implementations against it. Not the other way around.
A ProofNorth eval suite measures latency under load, interruption recovery, intent accuracy across accents and acoustic conditions, escalation triggers, compliance language adherence, and outcome resolution rates. It runs continuously in production, not just at acceptance testing.
We don’t take vendor referral fees. We have no incentive other than the right answer.
With clear success criteria and a real eval suite, vendor selection becomes a measurable exercise. Most voice AI vendor selections happen on demos, references, and pricing. None of those predict production performance.
We run your top 2-3 vendor candidates through the eval suite designed in Phase 2 and produce a quantitative comparison. In some cases, the answer is "build it yourself on a foundation model." In most cases, it’s a specific vendor with specific configuration changes.
A pilot is not a deployment. A pilot is a controlled experiment that produces data about whether and how to deploy.
The longest and highest-risk phase. We structure pilots in three stages: shadow mode (AI runs alongside humans, no customer impact), supervised mode (AI handles calls with human escalation paths), and production mode (AI is primary, monitored continuously). Each stage has gating criteria from the eval suite. No stage advances without quantitative proof.
We also build the operational infrastructure that production requires: monitoring, alerting, incident response runbooks, fallback procedures, and the human review processes that catch failures before customers do.
Production drift is the rule, not the exception. Without continuous evaluation, your voice AI quietly degrades until someone notices a customer satisfaction drop six months later.
Customer behavior changes. Call patterns shift. Underlying models update. Vendors push silent changes. We design and stand up the ongoing proof infrastructure: scheduled eval runs, drift detection, quarterly health audits, and the team practices that keep production AI accountable.
For clients on retainer, we run this layer for you. For clients who want to operate independently, we transfer the infrastructure and train your team to run it themselves.
We don’t sell voice AI platforms. We don’t take vendor referral fees. Our work centers on voice AI in production for mid-market contact centers. We take the occasional adjacent engagement when it fits, and we’ll tell you directly if it doesn’t.
Two-week AI Readiness Audit. Fixed scope, fixed fee, written deliverables your team owns.
Read the Method →