A cross-reference engine that tells your sales team which substitute SKU to sell the moment their preferred product is unavailable. A catalog powered by AI that classifies and standardizes 5,000+ product categories in months instead of a year. An automated product onboarding process that takes a new product from supplier to live eCommerce the same day it arrives.
A customer calls. Their preferred SKU is unavailable. Your sales rep checks two supplier catalogs, asks a colleague, and offers a substitute five minutes later, that the sales rep is not confident about.
It happens dozens of times a day. And it is not anyone’s fault. The AI cross-reference that should handle that moment in seconds simply has not been built yet.
We have built it for distributors in industrial MRO, plumbing, HVAC, dental supply… an AI-powered tool that maps equivalent, compatible, and substitute SKUs across every brand in the catalog, drawing on historical sales signals and returning a verified answer with a confidence score in seconds. A governed catalog that standardized 15,000+ attributes across 5,000+ categories in about four months, powered by AI, building the product layer everything else runs on. An automated pipeline that moves new products from supplier to live eCommerce the same day they arrive.
We have seen what breaks these projects and we know how to get them across the line. If any of that sounds familiar, we should talk.
Choosing the right partner for an AI and data program is as important as choosing the right technology. Here are four things that consistently make the difference when distribution programs succeed.
The cross-reference tool, the governed catalog, the supplier onboarding pipeline: all three depend on clean, unified product data. We build that as part of the delivery. You don't need a separate MDM (master data management) program to finish before the AI work starts. One team, one engagement, both problems solved.
Industrial MRO. Plumbing and HVAC. Dental and Animal Health distribution. We bring the specific AI-powered workflows already running in your category, the failure modes we've already resolved, and certified expertise across the cloud MDM, multidomain MDM, and enterprise integration platforms your AI runs on.
We build the supplier onboarding workflow that ingests, parses, and checks incoming data against your completeness thresholds. Qualified products publish to your eCommerce platform without a manual queue. New products arrive governed and go live the same day.
When a distribution AI project stalls, it almost always stalls on the same three things: attribute inconsistency, SKU mismatches across systems, and supplier data that cannot be trusted at scale. We have resolved each of these hundreds of times. We scope the risk in week one. Not in month four.
Distribution AI and data programs stall in predictable ways. Here is what we see most often, and what we advise.
The answer is a cross-reference capability that matches equivalent, compatible, and substitute SKUs across every brand automatically, so the alternative surfaces at the moment of the call rather than after it. Our recommendation is to drive those matches with AI across attributes, spec sheets, manuals, and historical co-purchase data, and to return a confidence score and rationale with each result so reps can trust it. Our experience tells us the accuracy of this approach compounds over time, since every verified match makes the next recommendation stronger and the system more reliable to sell from.
Attribute sprawl is a governance problem, and the answer is to reconcile the catalog into one standardized, deduplicated taxonomy rather than renaming fields by hand. Our recommendation is to use AI to analyze attribute patterns across the whole schema and propose a clean structure with a confidence score behind each decision. Our experience shows the payoff is significant: for an industrial MRO distributor, 18,426 attributes were reduced to 12,402, with 32.7% redundancy removed at 93.3% average confidence across 5,670 categories, in about four months instead of the usual 15+.
The answer is to automate intake at the source, checking supplier data against your standards on arrival instead of adding reviewers downstream. Our recommendation is an AI-assisted workflow that reads incoming catalogs, maps values to your fields, and validates each SKU against completeness rules, so records that pass publish automatically and the rest route to enrichment. Our experience shows the impact is immediate: for a leading Dental and Animal Health Distributor, this moved product publishing from three cycles a week to same-day, with every record arriving governed and consistent from the start.
Margin leakage here is a process gap, and the answer is to check every price change against your margin rules before it reaches the ERP, not after the damage is done. Our recommendation is an AI-assisted workflow that ingests every supplier format, matches part numbers to your internal SKUs, and validates each change automatically, so routine updates post on their own and unusual ones are flagged for review. Our experience tells us this is where governance matters most: every change stays tracked and reversible, and nothing reaches your books unverified.
Patterson Companies needed new products live on their eCommerce platform the day they arrive, not three publishing cycles later. Infoverity help build the PIM platform as the central hub, replaced fragile point-to-point integrations with automated connections to the ERP and eCommerce site, and built a supplier portal that feeds governed product data into the pipeline from the source.
Find equivalent, substitute, and replacement products across your entire catalog in seconds, with a confidence score and the reasoning behind each match. Reps and customers get the right alternative instantly instead of digging through catalogs or calling suppliers.
Product data from many sources is inconsistent: the same attribute named different ways, duplicates, and gaps. We reconcile it into one consistent, governed catalog in about four months instead of 15+, powered by AI and with a confidence score behind each decision.
Suppliers send data in different formats. AI reads each file, maps it to your fields, checks it against your standards, and publishes what qualifies, so new and changed products go live the day they arrive instead of sitting in a review queue.
Supplier costs change constantly. We create AI-powered workflows that ingest each price file, match items, and check every change against your margin rules. Routine ones post automatically, unusual ones get flagged, and every change is tracked and reversible before it reaches your ERP.
One governed record of your products, suppliers, and customers, connected to your ERP and storefront. The whole business runs on one version of the truth instead of a dozen conflicting copies.
Inventory, margin, and supplier performance usually sit in systems that never agree. This brings them into one real-time view, feeding your team and the AI tools from the same clean data.
Ready to get more of your distribution AI use cases actually live?
We start with your data: where it’s inconsistent, where it’s incomplete, and where it’s quietly blocking the use cases you’re trying to launch. Then we show you what’s possible once it’s fixed.
No obligation — a 30-minute conversation to understand where your AI and data strategy stands and where it could go.
