Turn account history into bigger online orders
Proton’s AI uses each account’s buying history to suggest products and reorders on your storefront, so buyers order without calling.
Acme Mechanical$242.404
PTFE tape, ½ in$1.85 ×12Added ✓
Pipe thread sealant, ¼ pt, 8 oz$9.60Add
Brass nipple, ¼ × 2 in$2.35 ×12Added ✓Pressure gauge, 2½ in$110.40×6PTFE tape, ½ in$22.20×12ProtonBrass nipple, ¼ × 2 in$28.20×12Proton
A4 cut nitrile glove$81.60×12ProtonA4 cut nitrile glove ×12Acme reorders every 30 days. Last order: 27 days ago.Shop through your buyer’s eyes
Find familiar items, compare alternatives and see what completes the order.
Acme MechanicalPut the next reorder in reach
Acme MechanicalDays since last orderA web order is only part of the picture
From distributors on Proton
“The AI-generated product recommendations in the customer portal are a big deal, since they give customers all sorts of helpful info as they check out different products.”
“The ROI on the e-commerce piece alone was immediate.”
“Seeing how Proton’s three key components — CRM capabilities, AI-driven insights, and website integration — overlap was eye-opening.”
Start with eCommerce AI, then add modules as needed
Use eCommerce AI with your existing storefront and ERP. Add modules that share account, product and order data with agents. Pricing AI, Inventory AI, Sourcing and Order Management are coming soon.
The storefront that sells like a rep
Recommend complementary products, in-stock substitutes, and items due for reorder using each account’s full purchase history.
Proton eCommerce AI adds personalized product recommendations and reorder reminders to a distributor's existing online storefront. It uses account purchase history from your ERP to suggest complementary products, similar items and products a customer may be due to reorder. Buyers get a more useful shopping experience, with less searching through the catalog.
Yes. Proton eCommerce AI learns from the orders in your ERP, including phone, email, counter, rep and web orders. A customer who usually orders through a salesperson can still receive recommendations based on that account's purchase history when they shop online. With site tracking, browsing, searches and cart activity add more context.
No. Proton eCommerce AI connects to your existing storefront through an API or widget. You keep the site your customers already use. Proton handles the integration in house, while your web team or platform partner coordinates storefront changes and places the recommendation carousels.
Proton connects to any ERP, so you can keep the system or systems you run today. Proton eCommerce AI uses connected order history and product data to find buying patterns and product relationships. Site tracking adds online behavior. During evaluation, bring a representative account and a few familiar products so we can review the data and recommendations together.
Proton eCommerce AI can show complementary products, similar items, new products and products an account may be due to reorder. Recommendations can appear on the homepage, product pages and in the cart or checkout. For repeat purchases, Proton uses the account's buying cadence to bring relevant products back into view before the next order.
Yes. Proton can tailor recommendation carousels to exclude specific products, categories or items an account has already purchased. Your team helps decide what buyers should see while the AI finds product relationships in the connected data.
No. Your storefront continues to show its own live prices and availability. Proton eCommerce AI supplies recommendations using the connected product and order data, while the storefront remains the source for what a customer can buy and what they pay. Adding recommendations does not require replacing your existing pricing or inventory systems.
Proton handles implementation and integration in house. Your team works with us on data access, recommendation placements, product exclusions and the tracking needed to measure results. Your web team or platform partner coordinates storefront changes. After launch, a dedicated Customer Success Manager helps your team review usage against the rollout's business goals. Timing depends on your data, storefront and scope.
RelaDyne reported 67% more regular customer-portal users after adding Proton eCommerce AI. R.S. Hughes reported well over seven figures in revenue attributed to its ecommerce recommendations.
With storefront tracking in place, Proton shows revenue influenced by each recommendation carousel, by account. Review that alongside order value, repeat purchasing and portal adoption. Agree on a baseline before launch and use a controlled comparison where practical to estimate additional sales.
Proton has a SOC 2 Type II report available for your security review, and your data is never used to train AI models. Before implementation, Proton will walk your IT team through the data involved, access and security requirements. That review gives your team a chance to assess how the proposed eCommerce AI connection fits your own policies before you launch.
More on B2B ecommerce
eCommerceE-commerce for distributors: the complete guide to selling online in 2026
Why portal sales never take off: the 70–80% data gap, why your platform matters less than you think, and how AI-powered recommendations close it.
eCommerceWhat are product recommendation engines?
How recommendation engines work, why Amazon's item-to-item model changed the game, and what it takes to make them pay off in distribution.
eCommerceeCommerce vs. distribution sales reps: why they need to work together
Buyers move between reps, phone, and self-service portal as it suits them. Why your technology strategy should back both channels instead of picking a side.
