Lanza Estudio
AI & Bots

The large quote bottleneck: AI to automate B2B RFQ processing

Steve

Steve

Senior Engineer & AI Specialist

"As an AI Specialist, it frustrates me to see B2B sales reps and technical sales engineers wasting entire days mapping endless Excels from corporate clients who request quotes using their own codes or weird descriptions. Taking three days to send an offer is the fastest way to lose the sale to a competitor. I build semantic AI Agents, powered by ultra-efficient models like Gemini 2.5 Flash, that read the Request for Quote (RFQ), understand what product the client is looking for, and match it to your exact catalog in seconds, ready to send."

Does your sales team waste entire days deciphering and mapping mile-long Excels from corporate clients just to send them a quote?

In the B2B market for supplies, spare parts, or electrical equipment, large companies do not buy through the online store. They send a Request for Quote (RFQ) in an Excel or PDF with hundreds of lines. The problem is that the buyer uses their own internal codes, competitor references, or vague descriptions. Your sales rep has to manually search every line in the ERP to find the exact equivalent in your catalog. This manual tracking delays the quote delivery, and in B2B, the first to quote is usually the one who wins the contract.

The trap of Standard ERP Search Engines

To try to speed up the process, sales reps use the management system's search engine, but these engines are rigid and require exact text matches. If the client asks for "halogen-free copper cable 2.5" and you have it listed as "Unipolar cable H07Z1-K 2.5mm Cu", the ERP finds nothing. Relying on a sales rep's visual memory to cross-reference divergent technical descriptions is a bottleneck that stifles your sales scalability.

Our solution: Semantic AI Mapping Agent for RFQs

At LANZA ESTUDIO, we turn complex requests for quotes into ready offers in seconds. We train semantic Artificial Intelligence models (like Gemini 2.5 Flash) that do not search for exact words, but rather understand the technical context of the product to match the client's list with your real inventory.

  1. Multi-Format Request Reading: The assistant reads the client's file (Excel, PDF, or email body) and extracts the requested product lines, ignoring the chaotic original format.
  2. Semantic Matching: The AI compares the client's description with your database, identifying technical equivalents, industrial synonyms, and competitor cross-references with maximum accuracy.
  3. Stock Verification and Substitutes: If the exact product is out of stock, the cognitive engine automatically looks for the best alternative or equivalent brand within your warehouse so as not to lose the sales line.
  4. Draft Quote Generation: The bot injects the matched SKUs, quantities, and your sales prices into your ERP's quoting module, leaving it ready for the sales rep's final review.

The Real Impact on your Corporate Sales

  • Quotes in Minutes, not Days: You multiply your sales team's response speed, delivering the quote to the client before the competition has even finished reading the Excel.
  • Increased Win Rate: By being the first to quote professionally and offering quick alternatives to stockouts, you earn the corporate buyer's trust.
  • Sales Team Liberation: Your star salespeople stop doing administrative work crossing codes in front of a screen and dedicate their time to negotiating and closing large accounts.
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