Applied AI · Intelligent Insights · Predictive Growth
Noevia Labs builds customer intelligence, predictive models, executive reporting, and production AI for organizations that need marketing and growth decisions made well, and made in writing.
Two decades of enterprise data science leadership, today at Fortune 1 scale. Two US patents in machine learning.
What we do
Each service has a full brief: what we build, how we build it, and exactly what you receive.
Board packs, KPI systems, and official documents built to production quality, where every number traces to its source.
The full briefRFM analysis, customer segmentation, lifetime value, cohorts, and pricing studies. Know exactly who buys, who stays, and who is worth pursuing.
The full briefForecasting, classification, document retrieval, and autonomous agents. Built from your business question down, validated honestly.
The full briefPropensity models that rank every lead by likelihood to close, calibrated into scores a sales team can actually use.
The full briefSerialization, versioned APIs, containers, and monitoring. On your infrastructure, or hosted and operated by us.
The full briefThe toolkit
Every method below is one we have run on real commercial data. If a term on this list is the thing your business needs and you didn't know its name, that's exactly what the first conversation is for.
Scores every customer on recency, frequency, and monetary value. The fastest honest answer to "who are our best customers, and who is quietly leaving?"
Clustering (K-Means and beyond) that groups customers by how they actually behave, so marketing stops sending one message to ten different audiences.
What a customer is worth over the whole relationship, not just the last invoice. Changes who you fight to keep and how much you spend to acquire.
Follows each customer class over time to show where retention breaks, and identifies which lapsed customers are worth winning back, and with what offer.
Time-series models for what sells, when, and how much, so inventory, staffing, and cash planning stop being guesses.
The probability that a specific customer buys, upgrades, or walks. Puts your retention budget on the accounts where it changes the outcome.
What gets bought together and what that means for bundling, placement, and cross-sell. The classic retail method, applied to any transaction data.
How demand actually responds to price, margin by product and channel, and pricing recommendations grounded in measurement instead of nerve.
Models that read free text: classifying descriptions, extracting structure, and retrieval systems that answer questions over your own documents with sources.
Proper hypothesis tests and experiment design, so "the campaign worked" is a measured claim instead of a hopeful one.
Statistical evaluation of where to open, close, or relocate: demographics, traffic, competition, and cannibalization, scored before capital is committed.
Models that flag the equipment likely to fail before it does, turning breakdown emergencies into scheduled maintenance.
Scores the likelihood and cost of the bad outcome, credit, claims, fraud, or project overrun, so exposure is managed instead of discovered.
Scheduling, routing, inventory, and allocation solved mathematically. The two granted patents in this house live in exactly this territory.
The full analytics ladder: why it happened, what happens next, and what to do about it, matched to the decision at hand.
A structured read of the whole business: where it stands, where you want it, and the measured steps between here and there.
Selected engagements
Healthcare · Fortune 500
A production retrieval system over more than 500,000 documents using vector search and LLM pipelines, giving analysts grounded answers instead of keyword guesses.
92% retrieval accuracy, in production.
Telecom · Regional operator
Market research and competitor analysis, financial models for product profitability and pricing, and daily KPI reporting delivered straight to senior management.
The morning numbers, on the executive's desk.
Sales operations · National brand
Multi-step reasoning agents that took over the manual qualification workflow for a national home-services brand, with cost, latency, and hallucination monitoring from day one.
60% of the workflow automated. Conversion up 23%.
Automotive services · Enterprise
An NLP model that maps free-text damage descriptions to structured categories, served through a microservices architecture built for scale.
Deployed on Kubernetes for a national operator.
How we work
Every engagement runs the same accountable pipeline, in this order, every time.
Founder & CEO
Noyle A. Christopher is the Founder and CEO of Noevia Labs, bringing more than twenty years of executive leadership in data science, AI, and marketing analytics. He serves as Senior Director of Data Science & AI at Walmart Inc., leading enterprise analytics and AI for Walmart Realty, and has built teams and platforms that have influenced billions in business decisions across retail, marketing, technology, and real estate.
At The Mars Agency he served as SVP of Data Science & Analytics and built the predictive marketing platform that led to the firm's acquisition by Publicis. He founded Noevia Labs to bring that caliber of applied AI to organizations that could never justify a Fortune 1 budget.
Connect on LinkedIn →"Noevia Labs turned our data into our competitive advantage."
— Sean Johnson, CEO, Deliver Media
Tell us what decision you're trying to make, what report you wish existed, or what process is eating your team's week. The first conversation is free and honest.
Request a consultation →Noevia Labs · Intelligent Insights. Predictive Growth.
