AI Quoting Software for Distributors (2026): Workflow and Tools

AI quoting software for distributors reads an RFQ in any format (email, PDF, spreadsheet, bid list, drawing or phone call), matches each line to your catalog, applies the customer’s contract price and live stock from the ERP, and hands a rep a draft quote to approve. Vendors report quotes that took 15 to 45 minutes by hand drafted in 60 to 90 seconds.

Built and proven in manufacturing plants, Morsa is now onboarding its first distributors. Morsa publishes this guide and appears in it. We put it where it honestly fits, and every vendor fact comes from the vendor’s own website, checked 24 September 2026.

Quick answer

• Industrial, HVAC or plumbing distributor on Prophet 21, Eclipse, Infor or DDI: Distro. Quote only.

• Fastener or industrial distributor with messy part numbers: BoltWise. Quote only.

• Building products quotes that start from drawings: HyperQuote, from $299 a month with unlimited users.

• Small supplier quoting from spreadsheets today: Quotable, from $49 a month ($37 billed yearly).

• Special orders stuck waiting on supplier prices, and quotes nobody follows up: Morsa runs that for your business. Now onboarding first distributors.

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In this guide

• What is AI quoting software for distributors?

• How does the quote workflow change with AI?

• Why does speed to quote matter?

• What does slow quoting cost a distributor?

• Which AI quoting tools should distributors compare in 2026?

• What should AI never decide in a quote?

• How do you run an RFQ automation pilot?

• Where does Morsa fit in distributor quoting?

• Bottom line

What is AI quoting software for distributors?

AI quoting software turns a customer’s request for quote (RFQ) into a priced quote without a rep searching the catalog line by line. It is different from CPQ (configure, price, quote) software, which is built for sellers of configurable products and dominates search results for “quote automation.” A distributor’s problem is not configuration. It is matching: a 200-line bid list full of abbreviations, competitor part numbers and “same as last time” against a catalog of tens of thousands of SKUs.

That makes match rate the number that matters. Proton.ai states the spread on its own page: “Internal builds plateau around 40%,” point solutions land at 60% to 75%, and “Proton matches 85% of products with 90% accuracy” (Proton.ai). Distro claims “95%+ accuracy” on product matching and “Hundreds to thousands of line items processed per quote” (Distro). Treat these as vendor figures to test on your own RFQs, not as benchmarks.

For orders that arrive already decided, the same technology is AI order entry; for the wider map, read AI for distributors.

How does the quote workflow change with AI?

A distributor quote has six steps. AI now drafts the first five; a person still owns the send.

1. Intake. The RFQ arrives by email, PDF, spreadsheet, drawing, phone call or counter conversation. Canals lets a rep “record the live audio and a quote is created as the conversation happens.”

2. Identify. Customer, branch, job and ship-to, from the email signature or the account.

3. Match. Each line to a SKU and unit of measure, with cross-references and ranked alternates where a line is ambiguous.

4. Price and check stock. Contract price, price matrix and margin floor from the ERP; stock across branches; supplier price and lead time for non-stock items.

5. Review. Low-confidence lines are flagged for a rep. At ChannelFlex, “Every line gets a confidence score”; high-confidence lines pass through.

6. Send and follow up. The rep approves, the quote goes out, and someone has to chase it until it becomes an order or a loss.

Step 4 for special orders and step 6 get the least space on vendor pages. Ventura promises to “Request supplier pricing, availability, and lead times” for special orders (Ventura), and Proton.ai “reminds reps when to re-engage” on open quotes. Most of the others stop at the draft.

Why does speed to quote matter?

Most sellers answer slowly, and slow answers lose. The best public evidence is older and about sales leads, not distributor quotes, so read it as a direction, not an exact effect. In a study published in Harvard Business Review in March 2011, James Oldroyd, Kristina McElheran and David Elkington audited 2,241 US companies: 37% responded to a web lead within an hour, 23% never responded, and the average response time among those that answered within 30 days was 42 hours. Across 1.25 million leads at 42 companies, firms that tried to contact a lead within an hour were “nearly seven times as likely to qualify the lead” as those that waited even an hour longer, and more than 60 times as likely as those that waited 24 hours or more. Their conclusion: “Companies are making big investments in order to obtain customer queries from the internet, and they should be responding at internet speed” (Harvard Business Review, March 2011).

Distributor evidence comes from vendors’ own customer stories, so it is one account each. Canals says one customer’s hit rate rose “from 20% on average to 57% for orders processed through Canals, a nearly 2.8X increase.” A customer quoted on Mercura’s site says: “Due to capacity constraints, we previously handled ~70% of incoming requests. We now handle 100% while improving customer satisfaction through faster quotes.”

What does slow quoting cost a distributor?

Illustrative calculation, not a Morsa result. Replace every input with your own numbers.

Inputs

• Volume: 40 RFQs a day, 250 working days, so 10,000 a year (an example distributor).

• Time to quote by hand: 15 minutes, the manual time Proton.ai publishes for one emailed request (“15 min → 60 secs”).

• Loaded cost per hour: $49.51. The median wage for wholesale and manufacturing sales representatives (except technical and scientific products) was $72,080 in May 2025 (BLS Occupational Outlook Handbook), or $34.65 an hour over 2,080 hours. Wages are 70.0% of private-industry compensation (BLS, June 2026), so $34.65 divided by 0.70 is $49.51.

• With AI: 2 minutes of rep review per drafted quote (Proton says 60 seconds and Distro 90 seconds; we round up).

• Revenue side: an average quote of $2,000 (assumption) and a 20% hit rate (the average the Canals customer above started from).

Result

• Rep time by hand: 10,000 x 15 minutes is 2,500 hours a year, or $123,764.

• Rep time with AI: 333 hours a year, or $16,502. About 2,167 hours, or $107,262, go back to selling.

• Unanswered requests: if your team answers 70% of RFQs today, as the Mercura customer did, the 3,000 unanswered requests a year are worth 3,000 x 20% x $2,000 = $1.2 million in orders.

• Hit rate: each point of hit rate across 10,000 quotes is 100 orders, or $200,000 a year.

The revenue lines are orders, not profit; apply your own gross margin. The time saving is real but small next to them. The money in quoting is in answering every request, fast.

Which AI quoting tools should distributors compare in 2026?

Eleven tools, ordered by how many distributor situations each fits, then Morsa. We read every fact and price on the vendor’s own site on 24 September 2026; where no price is published, the entry says “quote only.” For a wider field, including AP and purchasing agents, see the best AI agents for distributors in 2026.

1. Distro

Quick overview: “100+ Lines Quoted in Minutes.” Distro reads RFQs from PDF, Excel, email, images and handwriting, matches products with “95%+ accuracy,” applies “Customer-specific pricing and contract enforcement,” and syncs with “Prophet 21, Eclipse, Infor, DDI and more.” Its page says: “What used to take 45 minutes now takes 90 seconds.”

Best for: Industrial, HVAC and plumbing distributors on distribution ERPs.

Pros: Built around industrial distribution, and it suggests substitute and complementary products.

Cons: No price published.

Pricing: Quote only.

Source: distro.app

2. Proton.ai Order and Quote Entry

Quick overview: Turns “any inbound request into a ready-to-send quote or order,” with “90% Match rate accuracy across thousands of SKUs,” on the same platform as Proton’s CRM, PIM and ecommerce. It integrates with Epicor Prophet 21 and Eclipse, Infor SX.e, SAP S/4HANA and ECC, NetSuite and IBM AS/400.

Best for: Distributors that want quoting, CRM and ecommerce on one data set.

Pros: Published match-rate figures, an ERP list that reaches back to IBM AS/400, and follow-up reminders on open quotes.

Cons: A platform purchase, not a point tool.

Pricing: Quote only.

Source: proton.ai

3. Canals

Quick overview: Quotes and orders from email, phone and in person, where a rep can “record the live audio and a quote is created as the conversation happens.” It integrates with Eclipse, Prophet 21, Infor CSD, Infor SX.e, SAP S/4HANA and Microsoft Dynamics, and reports the 2.8x hit-rate case above.

Best for: Electrical and building supply distributors with busy counters and phones.

Pros: Voice quoting at the counter and in the field.

Cons: Quoting is one product in a wider suite; buy what you need.

Pricing: Quote only; “a tiered, usage-based pricing model.”

Source: canals.ai

4. BoltWise

Quick overview: “Return quotes 3-4x faster with AI-powered part matching.” BoltWise covers “1,000+ types of fasteners and 2,000+ types of other industrial goods,” cleans the catalog in week one, and integrates with Epicor Prophet 21, INxSQL, Infor CloudSuite Distribution and The Business Edge.

Best for: Fastener, MRO and industrial distributors.

Pros: Catalog cleanup is part of setup; a three-week rollout plan on its site.

Cons: Narrow by design; four ERPs named.

Pricing: Quote only.

Source: getboltwise.com

5. Ventura

Quick overview: AI quoting, order entry, takeoffs, order status and special orders for distributors and manufacturers, on Agility, Prophet 21, Eclipse, BisTrack, Business Central, Infor, NetSuite and SAP. “Customers typically go live in under three weeks,” and “Ventura has completed a SOC 2 Type II audit.” Ted Dometita, CFO of Richards Building Supply, is quoted: “We saw huge potential to reallocate sales capacity toward higher-value work.”

Best for: Building products and industrial distributors that want special-order supplier requests handled too.

Pros: Covers supplier pricing and lead-time requests for special orders.

Cons: Few published results beyond its customer quote.

Pricing: Quote only.

Source: ventura.ai

6. Mercura

Quick overview: AI quote and order automation for distributors and manufacturers, with “Voice Agents” that “provide real-time quotes,” spec and tender reading, and SAP and Oracle integration. Mercura says “60+ distributors and manufacturers trust Mercura” and lists “Y Combinator Batch W25”; servers are ISO/IEC 27001 certified and hosted in Europe.

Best for: European distributors quoting from specifications and tenders.

Pros: Tender and spec reading; margin-aware product suggestions.

Cons: Europe-first; check your ERP beyond SAP and Oracle.

Pricing: Quote only.

Source: mercura.ai

7. WizCommerce

Quick overview: An AI Order and Quote Entry Assistant that “Reads RFQs and POs from emails, PDFs, scans, voice messages, and handwritten documents,” flags missing fields and wrong prices, and creates ERP-ready orders through “1,000+ pre-built connectors.”

Best for: Wholesalers that sell through B2B ecommerce and reps.

Pros: Quoting sits inside a B2B ordering platform.

Cons: Less focused on large industrial bid lists.

Pricing: Quote only.

Source: wizcommerce.com

8. ChannelFlex

Quick overview: Reads inbound RFQs, matches “every line item to your catalog across all your vendor lines,” and scores each one: “Every line gets a confidence score.” It works alongside “NetSuite, SAP, Epicor, Infor, Sage, Salesforce and more,” with “real RFQs processed within two to four weeks of starting.”

Best for: Distributors quoting across many vendor lines.

Pros: Per-line confidence scores; RFQs and POs in one inbox.

Cons: Few published customer figures.

Pricing: Quote only.

Source: channelflex.com

9. Avent

Quick overview: An “AI Workforce for Distribution” that runs quote-to-cash on defined rules, AI and human approval. In its sample permissions, “The sales manager can approve quotes; the quoting agent cannot approve in this example.” It is SOC 2 compliant.

Best for: Distributors that want explicit approval rules around AI.

Pros: Workflows and permissions you can see and edit.

Cons: Few published customer results.

Pricing: Quote only.

Source: aventindustrial.com

10. HyperQuote

Quick overview: AI takeoffs and quoting for building product distributors: HVAC/R and plumbing drawings turned into bills of materials. It claims “90%+ Reduction in Takeoff Time” and “97%+ Equipment Tag Detection Accuracy,” with “Unlimited users and a 30-day free trial on every tier.”

Best for: HVAC/R and plumbing distributors that quote from drawing sets.

Pros: Published prices and a free trial.

Cons: Priced by pages processed; built for takeoffs, not emailed line lists.

Pricing: Starter $299 a month (200 pages), Team $599 (600 pages), Business $1,499 (2,000 pages), billed monthly; Enterprise custom.

Source: hyperquote.io/pricing

11. Quotable

Quick overview: Quoting, orders and payments for small suppliers, “Trusted by 400+ B2B teams across 30 countries.” The Pro Seller plan adds a “Universal AI/OCR Parser System”; Advanced Seller adds SAP, NetSuite, Oracle and Microsoft integrations.

Best for: Small distributors moving quotes out of spreadsheets.

Pros: The lowest published price here, with a free start.

Cons: Order caps (30, 100 or 500 a month) and lighter catalog matching than the distributor specialists.

Pricing: Starter $49 a month, Pro Seller $99, Advanced Seller $249; or $37, $74 and $187 a month billed yearly.

Source: getquotable.ai/pricing

12. Morsa

Quick overview: Morsa is the AI that operates the factory for you, and it runs the same daily operations work for wholesale distributors, on the systems the business already runs. For quoting, Morsa runs the work around the quote: chasing suppliers for special-order prices and lead times, following up open quotes, and turning a won quote into a delivery date that holds.

Best for: Mid-market and enterprise distributors whose quotes stall on supplier answers and follow-up, not on typing.

Pros: Works inside your existing workflow: email, WhatsApp, Teams or whatever your team uses. Cloud, private cloud or fully on-premise, including the AI models. Running in manufacturing: J4S, a 120-person glass plant, went live in two days with no new software.

Cons: Distribution customers: none yet (manufacturing live). Not a catalog-matching quote tool. No public price list.

Pricing: A pilot on one live problem first, free when no implementation work is needed; otherwise a minimal implementation cost, refunded if the pilot shows no value. The fee is a share of the value created, agreed after the pilot.

Source: J4S customer story and Morsa pricing

Summary

Turian and Conexiom also read quote requests alongside orders; both are quote only and covered in our AI order entry guide.

What should AI never decide in a quote?

Price, credit and substitutions belong to rules, not to the model. Brian Hopkins, Chief Operations Officer of Distribution Strategy Group and a former Grainger service center operations leader, put it this way: “Pricing, margin floors, credit limits, and product substitution are business rules. They must return the same answer every time, no matter which agent asks or how the question gets phrased.” And: “An agent is strong at conversation and context. It is a poor place to store your margin policy” (Distribution Strategy Group, 22 September 2026).

In practice:

• Price comes from the ERP’s pricing engine. A quote below the margin floor goes to a manager.

• Substitutions on spec-sensitive items go to a person. Hopkins: a wrong substitute “is not a rounding error. It is a failed job and a lost customer.”

• New accounts and credit terms never open from a quote.

• The send stays with a rep until your measured accuracy earns a change, line type by line type.

Ask every vendor to show the approval rule in the product, the way Avent’s sample permissions show a quoting agent that cannot approve.

How do you run an RFQ automation pilot?

Run the pilot on quotes you already know the answer to.

1. Pull 100 closed RFQs from the last six months, won and lost, across your messiest customers.

2. Clean the catalog first. BoltWise starts every rollout with a week of catalog refinement. Matching cannot beat your item data.

3. Score first-pass match per line, then the share of quotes sent with no edits. Compare against the vendor’s claim.

4. Time each quote from RFQ received to quote sent, before and after.

5. Run two to four weeks in shadow mode, with the AI drafting and reps sending as usual.

6. Track hit rate by quote age so you see whether faster quotes win more in your trade.

Stated go-lives on vendor sites are two weeks at Canals, under three weeks at Ventura, three weeks at BoltWise and two to four weeks at ChannelFlex. A one-month pilot fits all four.

Where does Morsa fit in distributor quoting?

Morsa is not a catalog-matching quote tool, and the tools above do that job well. Morsa runs what happens around the quote: the special-order line that waits three days for a supplier’s price, the quote that went out Tuesday and was never followed up, and the won quote whose ship date slips because a vendor pushed a PO. Those are coordination problems across people and suppliers, and they are where a fast quote still loses.

Our reference customer is a manufacturer, and we say so. At J4S, a 120-person glass manufacturing plant, on-time completion of operational commitments went from about 30% to about 75% in the first four weeks. Morsa went live there in two days, with no new software, no migration and no training. Anil Kohli, Production Head at J4S: “Our people don’t have to learn any new software. People just message the way they always have. Morsa coordinates all the messages in the background.” Read the J4S story.

For distributors we are onboarding our first customers now. Any system with an API, a database, an export or an email trail can be connected, whether that is your distribution ERP or a shared quote log. If you are still choosing that ERP, start with our distribution management software guide. A pilot on one live problem comes first (how pricing works).

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Bottom line

Buy AI quoting for match rate on your own RFQs, not for the demo. Distro fits industrial, HVAC and plumbing distributors on distribution ERPs; Proton.ai fits those that want quoting, CRM and ecommerce on one platform; Canals fits counter and phone quoting; BoltWise fits fasteners; Ventura covers special orders; HyperQuote ($299 to $1,499 a month) fits takeoffs from drawings; Quotable ($37 to $249 a month) fits small suppliers. Keep price, credit and substitutions in rules, and keep the send with a rep until the numbers say otherwise. The larger money is in answering every request and following every quote to an order.

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Sources

1. James B. Oldroyd, Kristina McElheran and David Elkington, “The Short Life of Online Sales Leads”, Harvard Business Review, March 2011

2. US Bureau of Labor Statistics, Occupational Outlook Handbook, Wholesale and Manufacturing Sales Representatives (median $72,080, May 2025)

3. US Bureau of Labor Statistics, Employer Costs for Employee Compensation, June 2026, released 9 September 2026

4. Brian Hopkins, “The AI Order Is Here. Decide What Your Agent Can Sign for Before It Can.”, Distribution Strategy Group, 22 September 2026

5. Distro quoting and order entry, 24 September 2026

6. Proton.ai Order and Quote Entry, 24 September 2026

7. Canals order entry and quoting, 24 September 2026

8. BoltWise and ERP integrations, 24 September 2026

9. Ventura, Mercura, WizCommerce, ChannelFlex, Avent, 24 September 2026

10. HyperQuote pricing and Quotable pricing, 24 September 2026

11. Morsa, J4S customer story

Changelog

• 24 September 2026: Morsa’s entry now names mid-market and enterprise distributors. Morsa is now described as the AI that operates the factory for you, and its entry, section and FAQ say what Morsa runs rather than what it builds.

• 24 September 2026: Published. Eleven quoting tools plus Morsa, every vendor fact and price read on the vendor’s own site on 24 September 2026; labor inputs from BLS releases of May 2025 and June 2026.