Turning an inbound email inquiry into a quote looks like one task and is actually four: read the email and its attachments into structured line items, match each item to your product catalog, apply the right customer’s prices and margins, and produce an offer clean enough to send. For a distributor’s sales office, that chain runs dozens of times a day, and today most of it is done by a senior rep with a spreadsheet open in one window and a PDF price list in another.
There is no single best email-to-quote tool; the right one depends on how much of that chain you need automated and how big your operation is. WizCommerce ranks first as the most complete engine, reading an RFQ in any format and turning it into a priced quote inside a full wholesale platform. OferIQ is the strongest focused fit for small-to-mid distributors, automating all four steps against your own catalog and pricing rules without an integration project. Proton.ai and Mercura are genuine AI-native quoting engines with wider platform or vertical scope; Conexiom and Esker are enterprise leaders at a neighbouring job — pushing emailed orders into an ERP — and Parseur is the honest baseline that extracts the data but leaves the quote to you.
Why “email-to-quote” is four jobs, not one
The reason so many tools claim to do this and so few do all of it is that each step fails differently. Parsing an email is now largely solved — modern AI reads free-text bodies and attachments well, and it is where extraction tools like Parseur stop. Catalog matching is where the difficulty jumps: a customer rarely writes “SKU-4472,” they write “the flexible conduit we used last project, connectors to fit our existing couplings.” Resolving that to real line items needs a system that understands your catalog by parameter, synonym and buying history, not a generic parser. Pricing is the step buyers most want kept honest: customer-group prices, volume thresholds and target margins should be calculated deterministically, not guessed by a language model. And the offer itself has to be trustworthy enough that a rep approves it in seconds rather than rebuilding it.
A tool’s real value is how many of those four steps it removes from a human. Extract-only tools remove one. Order-automation platforms remove the data-entry step at the far end of the deal. The tools that remove all four for the quoting stage specifically are a much smaller set.
The distributor case: why order automation is not quote automation
Two of the most capable platforms in this report — Conexiom and Esker — are frequently suggested when someone searches for turning emails into quotes, and they are excellent software. But their centre of gravity is the sales order: a confirmed purchase arriving by email that needs to become an accurate ERP transaction, validated against products, prices and stock, ideally without a human touching it. Conexiom is trusted for exactly this by firms like ExxonMobil and Fastenal; Esker reports more than 2.87 million orders automated monthly.
The quoting stage sits earlier and is a different shape of problem. Nothing is confirmed yet; the job is to interpret an ambiguous request, find the right catalog items, price them for that specific customer, chase any supplier prices you need, and produce an offer fast enough to win the deal. That supplier-RFQ loop — sending price requests out and folding the answers back into the offer — has no equivalent in an order-automation flow, because by order time the prices are already fixed. If your bottleneck is quoting, an order-automation platform solves the adjacent problem beautifully and leaves your actual one untouched.
What to check before you commit
Test on your own catalog, not a demo set. Match quality is the entire game, and it depends on your inventory and your customers’ phrasing. A vendor’s polished demo proves nothing about your data. OferIQ’s 30-minute demo runs live against your actual catalog and your own messy inquiries, which is the honest test; insist on the equivalent from anyone else on this list.
Separate the AI from the pricing. The safest designs let AI interpret and match, but calculate prices and margins in code from your rules — OferIQ takes exactly this approach, with customer-group rates, volume breaks, discounts and target margins applied in code rather than left to someone’s head. That keeps a language model from inventing a number and quietly eroding your margin.
Weigh the integration cost. Enterprise platforms assume an ERP integration project; that is a feature at scale and a barrier for a small office. OferIQ’s “works without API” approach — reading your existing PDF price lists as they are — is what lets a 3-to-20-person sales team start quoting in weeks rather than after a systems programme. Match the integration weight to the size of the team that has to live with it.
Assume you will pay after a demo. Only Parseur publishes pricing here. For everything else, get the all-in annual figure — implementation, minimums and any per-volume charges — before you pilot, and treat vendor speed claims as vendor claims until you have watched the tool run on your own inquiries.