Know whether your CX AI works before problems surface
An agent can handle thousands of interactions while resolution rates decline, bad answers go undetected, or the wrong cases get escalated. We build CX AI with measurement built in so you can see how it's performing and where it needs to improve.
Your contact center AI has been live for months, but do you know whether it's helping your resolution rate, or just handling volume?
Before the agent ships, we define what success looks like and how it will be measured. That includes resolution, escalation, answer quality, and the signals that tell you when performance is starting to decline.
What we can build for CX teams
Most AI initiatives fail after the strategy deck is delivered. PivotX stays through execution, adoption, and measurable business outcomes because that's where transformation actually happens.
AI agent evaluation with auditable evidence
50–70 pre-built metrics covering hallucination, KB retrieval, tool usage, escalation, compliance, and resolution, calibrated to your domain and risk tolerance.
Contact center AI with governance built in
Agents built with tracing, explainability, and human-in-the-loop review gates to identify issues and route the right decisions to people.
Patient and customer triage via AI
Symptom or inquiry assessment against clinical or service pathways, available continuously, reducing load on your human team and reducing wait time for the customer.
Sales and marketing funnel intelligence
End-to-end funnel visibility with ML-driven segmentation and propensity scoring to prioritize high-value pipeline and improve conversion.
Churn signals across product lines and channels
Signals that identify customers at risk of leaving while your team still has time to intervene.
Personalization with measurement
Personalization built on the factors that drive conversion, with measurement tied to the business outcome.
We define how your CX AI will be measured before we build it.
We start every CX engagement by defining what the agent should resolve on its own, what should be escalated to a person, and how performance will be evaluated over time. Those requirements shape the build and the week-ten deliverable. Ten weeks later, you have working MVPs in production with tracing, evaluation metrics, and human-in-the-loop review in place.
Explore & Evaluate
We map the business and identify where AI could create measurable value. Working with your team, we evaluate potential use cases and narrow the list to the ones worth pursuing. By the end of week four, we know what we're building, why it matters and how we'll measure success.
Validate
Solution design and prototyping happen alongside user involvement. The people who will use the solution help shape it as it develops. Working MVPs give the team something real to test and evaluate rather than asking them to react to a finished product.
Value & Scale
We deliver the working AI solution, a validated 12-month roadmap, and a quarterly execution plan. We also begin the process of putting the solution into use. At this point, your team has experience with the solution and a clear understanding of what comes next.
We help you define the problem precisely enough that the AI solution can be defended to your controller, auditors, and board. And we don't leave until you have AI in production, acting alongside your team.
CX AI with measurable results.
Related industries and other functions
Is your CX AI improving outcomes or just handling more volume?
Tell us how you're measuring today, and what you need to see to trust the AI is handling your customers the way you need it to. We'll show you how to measure what it's doing and where it needs to improve.