A customer sends an RFQ with a drawing, a spreadsheet, and a few specifications buried in an email. Your estimating team has everything they need to get started. Or so it seems.

Someone still has to open every attachment, pull out the relevant details, check for missing information, and make sure the request reaches the right person. If something doesn't match, it's another email, another conversation, and another delay before anyone can begin quoting.

For manufacturers and distributors handling a steady flow of requests, this preparation work adds up.

RFQ automation helps eliminate much of that manual work. With AI Agents, businesses can turn incoming emails, documents, and specifications into organized, ready-to-quote briefs, giving estimating teams the information they need to get started.

The Work That Happens Before the Quote

When businesses look for ways to improve their quoting process, they often focus on how quickly their team can generate a price.

But what about everything that happens before that?

An RFQ might arrive with several attachments, multiple product configurations, or specifications that don't quite match. The customer might reference an outdated drawing, leave out a required measurement, or request a delivery date without providing all the necessary shipping details.

Before an estimator can get to work, someone needs to make sense of it all.

That typically means reviewing emails, comparing documents, identifying missing requirements, and coordinating with sales, engineering, or other departments.

The problem isn't necessarily that any individual task is difficult. It's that these tasks consume time, require constant attention, and create opportunities for information to get lost between people and systems.

And as RFQ volume increases, so does the amount of preparation required.

What Does a Ready-to-Quote RFQ Actually Look Like?

Receiving an RFQ and being ready to quote it are two different things.

A request is ready for estimating when the relevant information has been organized, the necessary requirements are clear, and anything that still needs attention has been identified.

Depending on the business and product, that might include:

• Customer and project details: Who submitted the request and which account or project it belongs to.

• Product requirements: Part numbers, quantities, materials, dimensions, and configurations.

• Supporting documents: Drawings, specification sheets, and the correct document revisions.

• Delivery requirements: Requested dates, shipping details, and lead-time considerations.

• Outstanding questions: Missing information, conflicting specifications, or requirements that need additional review.

Without this information organized in one place, estimators spend valuable time gathering details instead of evaluating the request.

This is where automated RFQ intake can make a difference.

How AI Agents Handle RFQ Intake

AI RFQ processing goes beyond extracting text from a document.

Vsimple's AI Agents can work through incoming requests, organize the information, check it against defined business rules, and prepare the next steps in the process.

Turn Scattered Information Into One Clear Brief

Instead of having an employee manually review every file, an AI Agent can read incoming emails and attachments, identify relevant information, and organize it into a consistent format.

The Agent can extract details such as quantities, product specifications, drawing revisions, and requested delivery dates while connecting the request to the appropriate customer or project.

The result is a structured brief that gives the estimating team a clearer picture of what the customer needs, without requiring someone to assemble the information from scratch.

Catch Missing Information Before It Causes Delays

Even a well-organized RFQ can contain mistakes or incomplete requirements.

AI Agents can compare the information they receive against the company's established product rules and requirements, helping identify missing specifications, conflicting details, or requests that need clarification.

Rather than allowing those issues to go unnoticed, the Agent flags them and helps route the necessary follow-up to the right person.

That means estimating teams can see what needs attention before they begin their work.

Keep the Right People Involved

Not every RFQ can move straight into estimating. Some require engineering input, customer clarification, or a decision from someone familiar with the product.

AI Agents help coordinate those handoffs by preparing the relevant information and routing questions or exceptions according to the company's workflow.

Employees remain responsible for consequential decisions, including pricing, approvals, and customer commitments. The Agent handles much of the preparation and coordination that supports those decisions.

From a Customer Email to a Ready-to-Quote Brief

Consider a manufacturer receiving an RFQ from a distributor requesting 240 fabricated mounting brackets.

The email includes a drawing, a specification sheet, and a spreadsheet listing the requested quantities. The customer also provides a requested delivery date.

At first glance, everything seems to be there.

But the drawing is labeled Revision C, while the spreadsheet references Revision B. The customer also forgot to include a shipping address.

In a manual process, someone has to find those discrepancies, determine who should resolve them, and make sure the right information reaches estimating.

With an AI Agent configured for this workflow, much of that preparation can happen automatically.

The Agent reads the request and its attachments, identifies the relevant product details, and prepares a brief containing the customer information, quantities, specifications, supporting files, and delivery requirements.

It also flags the conflicting revisions and missing shipping address.

Instead of leaving those issues buried in the attachments, the Agent prepares the relevant information for engineering or sales to review.

Once the outstanding questions are addressed, the estimating team has a more complete, organized request to work from.

This is an illustrative example, but it shows the value of AI-assisted RFQ intake. The Agent isn't replacing the estimator's expertise. It's taking on the work required to get the request in front of them.

How Vsimple Makes RFQ Automation Possible

Vsimple helps manufacturers and distributors put AI Agents to work across the processes they already use.

With Vsimple's RFQ and Technical Intake capabilities, businesses can configure Agents to read incoming requests, extract product information, check specifications against business rules, and identify details that require attention.

The platform also helps connect those requests to the appropriate customers, projects, and employees, keeping the information and next steps organized as work moves between teams.

And because Vsimple's AI Agents work alongside existing business systems, companies can improve these workflows without replacing the ERP, CRM, or other tools they already rely on.

The goal is to give employees a better starting point, reduce unnecessary back-and-forth, and keep work moving without losing the oversight that important business decisions require.

More Quotes Start With Better Intake

Improving your quoting process doesn't always mean changing how your team calculates prices or generates proposals.

Sometimes, the biggest opportunity is improving the work that happens before either of those things begins.

When RFQs arrive with information already organized, requirements checked, and outstanding questions identified, estimating teams can spend more time doing the work that actually requires their expertise.

AI Agents make that possible by handling the repetitive preparation and coordination that often slows the process down.

Have an RFQ process that's taking too much time? Explore Vsimple's AI Agents and see how they could help your team turn incoming requests into work that's ready to quote.

Frequently Asked Questions

What is RFQ automation?

RFQ automation uses software to handle repetitive steps involved in receiving, organizing, and processing requests for quotation. AI-powered workflows can also extract information from documents, check requirements, and prepare requests for review.

Can AI Agents process RFQs with multiple attachments?

Yes. AI Agents can be configured to read supported document formats, organize information from multiple files, and identify missing or conflicting details. Results depend on document quality, the configured workflow, and the information available.

Does RFQ automation replace estimators?

No. RFQ automation helps estimators by preparing the information they need and identifying issues that require attention. Estimators remain responsible for evaluating requirements and making pricing decisions.