Proton Answers

Proton is an AI platform built for wholesale distributors. It helps them grow revenue faster and lower operating costs by connecting the ERP and the rest of their business data into one shared data layer, with AI agents doing real work on top of it across sales, product data, ecommerce, and quotes and orders.

The platform is made of modules: CRM, PIM, eCommerce AI and Quote & Order Entry Automation. Distributors start with one and add more over time, and every module shares the same data, so each one gives Pronto, Proton’s AI teammate, and your agents more to work with.

For a sales rep, that can mean a customer’s purchase history beside a spending gap or an overdue quote. For a product-data team, it can mean filling missing specifications with a cited source for every value.

AI can help distributors identify selling opportunities, improve product data and prepare quotes or orders. Useful applications start with a concrete task: finding an account that is buying less, locating missing specifications in supplier documents, or matching lines from a customer’s PDF to catalog items.

Each task needs different inputs and checks. A sales recommendation needs purchase history and account context. Product enrichment needs traceable sources and review. An order draft needs a person to resolve uncertain matches and approve the result. Choose a workflow where the team can inspect the output and measure whether it improves the work.

Proton is built for wholesale distributors managing broad catalogs and ongoing customer relationships. Its published customer base includes family businesses and public companies. Examples include Aquifer in HVAC and plumbing, and Swish in cleaning and sanitation.

Evaluate fit through the work your team needs to improve. Do reps need a shared account history and clearer follow-up? Is product information scattered across supplier files? Does the ecommerce team need more relevant recommendations? Your catalog, sales channels, connected systems and rollout capacity help define the evaluation. Bring representative accounts and products so the demonstration reflects how your business operates.

Yes. You can start with any module, whether that’s CRM, PIM, eCommerce AI or Quote & Order Entry Automation, and add others later.

Choose the first module based on your business priorities: rep preparation and follow-up, supplier-data enrichment, online product recommendations, or retyping inbound quote and order requests. Every module runs on the same data layer, so the next one you add builds on the connection and data already in place. Give the first rollout a clear purpose and a result to measure, then expand from there.

Proton is an AI platform. CRM and PIM are two of its modules, alongside eCommerce AI and Quote & Order Entry Automation. Every module runs on the same data layer, built from your ERP and your other systems, and Proton’s AI agents work across all of them.

CRM covers customer relationships and selling: account preparation, opportunities and follow-up. PIM covers product information: specifications, attributes, descriptions and catalog organization. Because the modules share one data layer, every module you add gives Pronto and your agents more to work with. Start with the module that matches your most pressing problem and expand from there.

Pronto is Proton’s AI teammate for distribution teams. Reps ask out loud or type, and Pronto answers from your live ERP and business data, then does the work, such as drafting the follow-up, logging the visit note or building the call list, for a person to approve.

Pronto is built into the Proton platform, and each module you add gives it new tools, like your book of accounts from CRM or drafting from Quote & Order Entry Automation. Unlike general AI tools, it can see your ERP and act in your systems. It never acts on its own: a person approves every email, note or quote, and every action is logged. Customer data is never used to train models.

Proton’s AI agents are always-on assistants that take on repeatable work for distribution teams. They run on a schedule, when something happens in your ERP, or when a condition is met, such as a quote sitting open for seven days, and have drafts waiting for your team by morning.

Agents chase quotes, past-dues and POs using the ERP data already in Proton (orders, quotes, customers, items and pricing), plus any connected tools you turn on. Anyone on your team can build one: describe the job in plain English, choose what it can read and set when it runs. Agents never send anything to a customer on their own; they draft the email, quote or follow-up, and your rep reviews and sends it. Pronto works with you in real time; agents work the night shift.

Proton CRM. It’s built for distributors and is one module of the Proton platform, so it shares one data layer with your ERP and with Proton’s other modules (PIM, eCommerce AI and Quote & Order Entry Automation), while Pronto and AI agents work across all of them.

That shared data shows up in a rep’s day. Products a rep pitches come with full specs from PIM, what an account browses and buys online appears on the account view, and quotes drafted from emailed RFQs land in the rep’s pipeline with a follow-up task, so no quote goes cold.

It’s also built so reps actually use it. Reps open a ranked call list and drafted follow-ups instead of a blank record, the account fills in from your ERP so there’s no manual data entry, and on iOS and Android they can dictate notes and prep visits between stops. Across Proton distributors, products Proton flags get reordered 1 in 3 times after a rep’s call, compared with 1 in 10 for a lapsed product picked at random.

An ERP records the transaction; a CRM helps the sales team decide what to do before the next one. A distributor may know what a customer bought without having a shared plan for an unreturned quote, a shrinking product category, or the next account visit.

Proton connects ERP history with account activity and sales opportunities so reps can work from the same context. The useful test is practical: can your current setup show a rep whom to contact, why, and what to discuss? If it already does that well and your team uses it consistently, investigate the remaining gap before adding another system.

Distributors need reliable analysis and a way to manage customer relationships, but those capabilities do not always require two separate products. BI helps a team investigate performance; CRM organizes customer activity and the next sales action. Some platforms include both.

A sales leader might need a branch profitability report, while a rep needs to know which customer to call about an open quote. Evaluate those jobs separately. List the reports your managers actually use, the actions reps need to complete, and which tools already cover them. Proton CRM includes reporting alongside sales workflows, so assess the remaining analytics requirements before adding a separate BI subscription.

Proton surfaces accounts that need attention and the reason to contact them: a change in buying activity, a missed reorder, an open quote or an opportunity to sell more into an existing account.

Vallen’s published deployment includes customer health signals, reorder reminders and recommendations informed by similar customers’ purchases. Those signals give a rep a starting point for the day. The rep can then bring in context the data may not capture, such as a customer’s shutdown, a project deadline or a conversation yesterday. A useful priority includes a clear reason to act and room for the rep’s judgment.

Compare an account’s purchases with related products and the buying patterns of similar customers, then investigate the gaps. A customer buying one part of a product category may have a need for complementary items your reps have never discussed.

For example, a contractor buying pipe may also need fittings—but the rep should confirm the application, specifications and buying arrangements before making a pitch. Proton’s published building-materials story describes suggestions for products commonly purchased together. The value is a relevant conversation starter across a catalog too large to memorize. A recommendation points to an opportunity; the customer conversation establishes whether it is a fit.

Proton surfaces at-risk accounts and changes in purchasing so reps can investigate before a customer disappears from the order book. The signal is a reason to look closer, not proof that the customer has switched suppliers.

In Chattanooga’s published story, a drop in purchases from one brand prompted a conversation that uncovered an online visibility problem at the customer. The cause mattered: a discount would not have fixed it. When a flag appears, review the affected products, order history and recent conversations, then ask what changed. The answer may point to lost share, a service issue, seasonality or a genuine change in demand.

Proton gives reps visibility into quotes and reminders to follow up, so a bid can stay part of the sales workflow after it is sent. The published building-materials story describes timed alerts that prompt inside and outside reps to contact the customer.

Make the follow-up specific: is the customer still waiting on project approval, checking a specification, or deciding when the material must arrive? Give the quote an owner and a next action, and record the response where the rest of the team can see it. The handoff matters when a quotations team prepares the bid and an outside rep owns the relationship.

A mobile CRM should help a rep prepare for the next visit, capture what happened at the last one, and leave a clear next step for the team. That means useful account history, recent interactions, tasks and a practical way to record notes from a phone.

Aquifer’s published story describes outside reps using Proton mobile to review tasks, order history and recent interactions while traveling between customers. Test a normal visit in a demo: find the account, review the context, record the conversation and identify the follow-up. Judge the workflow on the phones your reps carry, using the information they need in the field.

Start with a job reps want to finish, and make the CRM a useful part of completing it. Preparing for a visit or following up on a quote gives the first training session a concrete job to complete.

Use the team’s own accounts, involve respected reps early, and have managers use the same records in coaching. Swish’s published rollout combined leadership involvement, internal champions and ongoing training. Measure whether the chosen work gets done: are visits prepared, notes shared and follow-ups completed? If reps still have to hunt through other systems for essential information, fix that friction alongside the training.

Yes. Reps can use voice interaction with Pronto to capture a customer visit note in Proton, which reduces the need to type a recap on a phone after every stop.

A useful spoken note names the contact, what the customer needs and the agreed next step. For example: “Met Ana about the new maintenance line. Send the filter specifications tomorrow and check back after her team reviews them.” Review the captured note before saving it, especially names, part numbers and dates. The goal is an account record that inside sales and the next person covering the territory can understand.

Product information management (PIM) software organizes the descriptions, specifications, images and categories that help a distributor sell its catalog. It gives product, ecommerce and sales teams a shared place to maintain information supplied in many different formats.

For a distributor, the work includes deciding which attributes belong in each product category, checking their completeness and preparing content for selling channels. A bearing needs different fields from a cleaning chemical. Evaluate PIM with a representative slice of your catalog: can the team find missing information, review changes and produce records that your website and sales tools can use?

An ERP manages the operational side of a distributor's products, including item records, purchasing, inventory and transaction pricing. A PIM manages the richer product information people need to find, compare and select those items: specifications, descriptions, images and category attributes.

The systems need agreed responsibilities. For example, an ERP item number can identify the product while the PIM supplies the dimensions and images shown online. Define which system owns each field and how updates move between them. Adding PIM should not create competing versions of price, stock or product identity.

Proton PIM finds product information in sources such as manufacturer websites, PDFs and catalogs, then organizes it into structured attributes. Its published workflow includes source citations, normalization and review so the product team can check the information before approving it.

Begin with a category whose data requirements are clear. Agree on the required attributes, units and output format, then review a sample containing both well-documented and difficult products. Keep the source attached to technical details. A blank field that needs supplier follow-up is more useful than a plausible specification nobody can substantiate.

Define the product structure you want before combining supplier files. For each category, specify the required fields, units, allowed values and product identifiers. Map each supplier's columns into that structure, normalize formatting and route conflicting or incomplete values for review.

Keep the original source alongside the standardized value so your team can trace a change. Similar field names do not always mean the same measurement: a product's outside diameter and its connection size should remain separate. Assign an owner for the rules and test them as new supplier files arrive. Standardization is an ongoing catalog process.

Yes. AI can draft product descriptions from verified specifications and extract attributes from supplier documents. Those are different tasks: rewriting known facts into readable copy does not establish a missing technical fact.

For a distributor's catalog, keep dimensions, materials, ratings and compatibility tied to supporting evidence. Review generated text for claims the source never made, especially when similar products differ in one important specification. Proton PIM finds the specs your catalog is missing, writes the descriptions and cites a source for every value, and your team approves the result.

Recommendation engines rank products using signals such as purchase patterns, product relationships and browsing behavior. For distributors, the relevant history can include orders placed through reps, counters and phones as well as online.

Proton eCommerce AI combines ERP purchase history with ecommerce data to suggest complementary products, alternatives and items due for reorder. Evaluate recommendations against the customer's actual application and buying context. A suggestion to replenish a consumable and a suggestion to substitute an engineered component need different checks. Measure useful purchases and order value alongside clicks, and verify product suitability before treating an alternative as interchangeable.

Search should support both a buyer who knows the exact item and one who can only describe it. Prioritize exact SKU and manufacturer-part-number matches, account for common spacing or hyphen variations, and use descriptions, attributes and relevant synonyms to help with broader requests.

Keep distinct product codes distinct. For example, a search for AB-102 should not silently become AB-120. Test real customer queries against your catalog, including partial codes and incomplete descriptions. Where the request could identify several items, show the differences or ask for clarification before the buyer selects a product.

AI order entry turns a customer’s request into structured order information, reducing the line-by-line retyping that follows an email, PDF or spreadsheet. It can identify requested items and quantities, match them to catalog records, and prepare a draft for review.

For a distributor, reading the document is only the beginning. A customer’s part number may differ from your item number, or a requested quantity may use a different selling unit. Evaluate the whole path from the original request to the reviewed order, including how the system handles information it cannot resolve.

Proton’s Quote & Order Entry Automation reads incoming requests, matches each line to your catalog and prepares a draft quote or order for a rep to review. It reads email body text, PDF attachments, Excel and CSV spreadsheets, handwritten notes, web forms, EDI feeds and competitor part-number lists, and uses customer pricing and inventory context.

For an inside sales team, that changes the starting point: the rep checks proposed lines instead of building every line from scratch. Keep the distinction between preparing a draft and resolving an exception. An unclear item description, unusual quantity or unconfirmed price still needs a defined decision before the customer receives a commitment.

Yes. AI can extract the requested products and quantities, propose catalog matches, and prepare structured order lines for review. Proton includes email and PDF intake in its documented workflow.

The request’s intent still matters. An RFQ asks for pricing; a purchase order asks you to supply goods. The workflow should preserve that distinction, confirm the customer and ship-to, and route unresolved details to the right person. Creating or submitting an order record is a separate step from reserving stock, releasing a credit hold, picking and shipping it.

It should preserve the requested quantity and selling unit, apply the configured conversion where appropriate, and make the result visible for review. Two cases containing twelve pieces each mean twenty-four pieces; two individual pieces are a different order.

A useful draft shows the original request, matched item, requested unit, converted quantity and price basis together. If the unit or pack size is ambiguous, the line should wait for confirmation. Test cases, eaches, lengths and partial packs using your own ERP configuration rather than assuming that a correct product match also means a correct quantity.

In Proton’s documented workflow, the rep reviews the prepared draft before approval. Items the system is less confident about are flagged for confirmation.

Use that checkpoint to check the proposed product, quantity, unit, customer price and delivery assumptions against the original request. Your rollout should also identify who can approve an exception and which action sends the quote or submits the order. Reviewing a draft, committing a transaction and fulfilling it are different decisions; a clear approval step should tell the rep which one they are making.

It should use the agreed pricing source, show which branch or warehouse supplies availability, and preserve the order controls your business relies on. A missing customer price should trigger clarification. Stock shown at another branch should not become an unexplained delivery promise.

Credit checks also need an explicit home in the workflow: ERP systems can apply configured holds before an order proceeds. Proton’s published quote flow uses customer pricing and inventory inputs, but a rollout still needs field-level agreement on freshness, exceptions and approvals. Test a contracted price, a backorder and a customer on hold before enabling the workflow.

ERP manages the operating records behind a distributor’s business: orders, inventory, purchasing and financial transactions. CRM organizes customer relationships, sales activity, opportunities and follow-up. Some ERP products include CRM features, so the useful comparison is the work each system helps your team complete.

For example, an ERP may record a customer’s purchases while CRM connects that history with the rep’s visit notes and next action. Proton connects ERP context with selling workflows. Evaluate how the systems share customer and product records, and which remains responsible for transaction updates, before deciding what to add.

Proton works with any ERP, or several at once, including Epicor P21, Epicor Eclipse, Infor SX.e and NetSuite. Proton’s forward deployed engineers build the connection, and your ERP stays the system of record.

The connection still needs to fit your environment. Confirm your ERP version and hosting setup, the customer and product records needed, the refresh schedule, and whether the workflow requires reading data or writing changes back. A sales-history feed and an approved order-entry connection have different requirements. Bring representative records and workflows to the integration discussion so the scope covers what your team actually needs to do.

For purchase-based sales insights, start with customer and ship-to records, product identifiers, and dated transaction lines that connect the two. Quantities, selling units and sales values help a rep understand what an account buys and how that changes over time.

Then add the data needed for the workflow. Quote follow-up needs quote identifiers and a dependable status; a pricing discussion needs the relevant customer prices; product recommendations need usable item information. Define which records are required, who owns them and how much history is available. Test a few real accounts—including returns, duplicate records and different ship-to locations—before expanding the feed.

A multi-ERP CRM project needs agreement on how customer, product and branch records relate across systems. The same account may have different IDs after an acquisition; the same SKU may be represented differently at two operating companies. Decide which records should be combined and which must remain separate.

Proton works with several ERPs at once and brings them into one data layer. For a multi-ERP evaluation, ask the team to demonstrate your account hierarchy, item mapping, permissions and data refresh requirements using representative records. Also specify which system owns each field and whether information is read-only or written back.

Define the refresh requirement and direction for each record type. An account’s sales history, today’s inventory and a newly approved order serve different decisions; they may need different update schedules and controls.

With Proton, your ERP remains the system of record for orders, pricing and inventory, and what Proton reads and writes depends on the connection. During scoping, document which records move in each direction, how often they update, who can change them, and how failed updates are handled. For quote or order workflows, a rep approves each draft before it is submitted to the ERP; agree what confirms that the ERP accepted the transaction. These details should be demonstrated for your environment before reps rely on the connection.

Review how a vendor protects the information your sales team uses: customer pricing, margins, contact details and order history. Ask for evidence covering access controls, encryption, hosting, customer separation, testing and incident handling. Include the ERP connection and any AI providers in that review.

Proton’s Trust Center lists SOC 2 Type II and describes Google Cloud hosting, encryption in storage and transit, logical customer separation, quarterly vulnerability scans and annual external penetration tests. IT teams can request supporting security documents there. Review the report’s scope and the controls relevant to your proposed deployment as part of the evaluation.

Ask who can use your data, for which purposes, and what control you retain. For AI features, establish which model providers receive information, what they retain, and whether customer data can be used to train or improve models. Also address access, exports and deletion.

Use a concrete example: a quote request containing customer-specific prices and contact details. Trace where that information goes and which terms apply at each step. With Proton, customer data is never used to train AI models. Proton’s Trust Center lists the current model providers and subprocessors; review those materials alongside your agreement to establish the terms for your deployment.

Less than most teams expect. Proton connects your ERP and builds the data layer for you, so there’s no cleanup project to finish before you start. Focus the cleanup you do on the records needed for the first workflow. For account insights, check that customer and ship-to IDs connect to dated sales lines and that duplicate accounts do not split the history. For product matching, check item IDs, manufacturer part numbers, descriptions and selling units.

After an acquisition, decide which customers and items represent the same thing and which should stay separate. Assign an owner for those mappings and for new records added later. Test a representative sample with the implementation team, then prioritize the issues that affect the pilot.

CRM cost includes software, implementation and the work required to keep the system useful after launch. For a distributor, ERP connections, customer and ship-to records, transaction history, branch structure and rep access all shape what needs configuring and testing. Budget internal time for data ownership, training and sales management, too.

Compare proposals on the same scope: included users and features, integration and migration work, training, support and any additional usage charges. Ask who maintains each connection and what happens when your ERP changes. Separate one-time costs from recurring costs so a lower subscription price does not hide a larger project.

Proton’s published CRM comparison guide reports an average go-live time of 12 weeks. Your timeline depends on ERP access, data mapping, the sales workflow and how many teams are launching. A rollout for one team has fewer decisions to coordinate than a project spanning several operating companies and ERP systems.

Ask for a current schedule with separate milestones for data access, record validation, configuration, rep training and rollout. Agree who owns each step and what must pass before the next one begins. Test representative accounts, products and quotes. Treat technical go-live and consistent rep adoption as separate milestones; having the data connected is only part of a working sales process.

Start with a baseline for the participating accounts and reps. Track adoption, then business outcomes such as customer retention, quote conversion, sales per rep and gross profit. Account for seasonality, price changes and territory changes when comparing periods.

A practical calculation is ROI = (incremental gross profit + realized operating savings − total project cost) ÷ total project cost, with every term measured over the same period. Include software, implementation and internal effort. Avoid counting the same benefit twice.

Keep attributed revenue separate from incremental growth. Attribution links a sale to an activity under a tracking rule; it does not prove that activity caused the sale. A phased rollout or comparison group can strengthen the estimate. Count saved time as cash savings only when spending actually falls.

Proton’s published customer stories report results in revenue, order value and rep productivity:

• Aquifer:average monthly revenue increased 34% and average order value increased 47% since adopting Proton in 2023.
• Vallen:sales per inside rep increased 72%.
• Swish:$3.2 million in revenue attributed to Proton.

Each story describes a particular distributor’s experience. Read the workflow behind the result, then compare it with your own baseline and rollout plan. Preserve the metric’s meaning: Swish’s attributed revenue is different from measured incremental growth, and Vallen’s rep-productivity result is different from company-wide revenue growth. These figures are evidence to assess, rather than a forecast for every implementation.

Keep your current CRM if reps use it, account information is shared, important follow-ups happen and managers can connect the work to business results. Before replacing it, test whether the remaining gap can be solved through a better ERP connection, a simpler workflow or clearer ownership.

Defer a new implementation if no one can own data access, rep training and the operating routine after launch. An ERP migration or acquisition can also make a phased project more practical than a full rollout. If the urgent problem is missing product specifications or slow order entry, evaluate that problem first; replacing CRM may not be the first project to fund.

Keeping your CRM doesn’t rule Proton out. Your ERP, CRM, PIM and web store keep running, and Proton connects them, so you can start with another module, such as PIM or Quote & Order Entry Automation, and leave the CRM decision for later.