Build With Less AI

How to Automate B2B RFQ Responses Using AI (Without Hiring Sales Reps)

AI Export Lab · July 27, 2026

A real workflow for auto-matching OE numbers, generating quotes, and replying to buyer inquiries using AI. Built and running on a live B2B export site.

AI Export Lab | July 27, 2026

Here is a problem every small B2B exporter knows:

A buyer sends an email: "Hi, do you have OEM BJ-3-12? Price for 200 units FOB Shanghai?"

The email sits in your inbox for two days. You finally open it, open the product catalog, Ctrl-F the part number, dig up the price list, type a reply, hit send.

Now multiply that by ten emails per day. Twenty. Thirty. While you are also packing orders, arranging shipping, and arguing with the factory about a delayed container. That is the life of a small exporter who sells at volume.

I run jjradiator.com, a B2B auto parts export site with 15,000 product pages and 112 registered customers. I am not a sales team. I am one person. When the site started getting inquiries, I realized pretty fast that I could spend my entire afternoon just replying to emails — or I could make the AI do it.

So I did.

The system I built now auto-reads an inquiry, finds the matching product, generates a quote, checks the reply against a list of 15 banned word categories (compliance problems you do not want in a B2B export email), and drafts a response. I review it, maybe tweak two lines, and send. Total time per inquiry: under one minute.

Here is exactly how it works.

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The Problem: 30 Inquiries, One Person

Raw numbers from jjradiator.com traffic:

Fifteen minutes times twenty inquiries is five hours. That is a full working day.

The bottleneck is not finding the product. The bottleneck is the sequence: find, check, price, write, review. Every step has a micro-decision. Every micro-decision slows you down. AI removes them.

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The Solution: AI Reads, Matches, Quotes, and Checks

The pipeline has four stages:

  1. Read. AI extracts the OE numbers, quantity, and delivery terms from the email body. It handles typos ("BJ312" instead of "BJ-3-12"), partial numbers, and mixed-language emails.
  2. Match. AI queries the product database for each OE number and returns the product name, dimensions, core size, material, and weight.
  3. Quote. AI references the price table, calculates FOB unit price and total, and generates a formatted quote block.
  4. Scan. A compliance scanner checks the draft reply against 15 word categories before anything is sent — product liability terms, guarantee language, country-specific restrictions, export control keywords, and price-commitment phrases that create legal obligation.

The scanner is the part most people skip. In B2B export, a single sentence like "we guarantee delivery within two weeks" creates a binding obligation. In auto parts, a sentence like "this fits all models" creates liability. I learned this the hard way. The scanner catches these before the email leaves my drafts.

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The Setup (Copy This)

You need three things:

The total cost per inquiry is under ¥0.10. That is one-tenth of a yuan to do what a human does in 15 minutes.

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What It Cannot Do (Yet)

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For Small Exporters: Where to Start

Do not build the full thing on day one. Start with step one:

Give the AI your product database and tell it: "When I paste an email, extract the OE numbers and find matching products."

That alone saves the Ctrl-F step. That alone is already 40% of the time per inquiry.

Add quoting next week. Add the banned-word scanner the week after.

The pattern is the same as the manager-worker pattern I wrote about: you do not need to solve everything at once. You need to remove the slowest step first, then the next slowest, and so on.

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If you are running a small B2B export site and spending hours on email replies, this is the single biggest lever you have. It does not require a developer. It requires a database, an API key, and one afternoon of setup.

Have questions about the setup? Use the contact form. I reply to every message about this topic.