If quoting is slowing your business down, it’s time for an upgrade. This walks through how an AI agent can read RFQs, create and send quotes, follow up with customers, and even help you win more deals—without hiring. You’ll see how it saves time, increases revenue, and helps your business grow—without the growing pains.
Quoting is one of those jobs that gets more painful as you grow. More customers. More requests. More quotes. But unless you’re adding team members just to handle quoting, you’re going to hit a wall. That’s where AI quoting agents come in—not just as tools, but as teammates that can actually close deals. Let’s walk through what they are, why they’re different, and what makes a great one.
Why Quoting Slows So Many Manufacturing Businesses Down
If quoting feels like a never-ending game of catch-up, you’re not imagining it. In a typical week, you might have 20 RFQs come in—some from current customers, others from new prospects. Each one is a little different. Some are complete and detailed, others are vague or missing key specs. Every one of them needs attention.
Let’s say you get an RFQ for 10,000 custom-machined aluminum parts. It’s a great opportunity—but someone has to review the specs, check inventory, run the numbers, and write the quote. Then it has to be emailed back, ideally with a friendly note that makes the customer feel like a priority. And then what? Wait? Follow up? Hope they didn’t already go with someone else?
Multiply that by 20 or 30 requests a week, and it’s no wonder things fall through the cracks.
For a lot of manufacturing businesses, quoting becomes a bottleneck long before production does. You can have a world-class shop and still lose deals because you were too slow, too busy, or too understaffed to respond on time.
Now here’s the bigger insight: quoting isn’t just about speed. It’s about capacity. You don’t just need to move faster. You need a way to handle more opportunities without burning out your team or hiring three more people. That’s the real shift an AI agent can deliver.
Take a hypothetical example: a mid-sized contract manufacturer in Indianapolis that handles precision components. They used to respond to 60–70% of RFQs, max. Not because they didn’t want the work—but because that’s all their quoting team could handle. After deploying an AI quoting agent, they started responding to nearly every request within 24 hours. Their close rate jumped 12% in the first quarter. Same production capacity, more work coming in the door. That’s not a tech win—it’s a business win.
And here’s what makes it work: the AI agent doesn’t just automate. It communicates. It reads the RFQ, builds the quote, sends a response, and follows up. It knows your pricing, your margins, your product rules—and it gets better over time. You’re not babysitting it. You’re letting it run a process your business already needs to run better.
An AI Agent That Closes Deals—Not Just Drafts Quotes
There’s a big difference between a tool that drafts quotes and one that drives revenue. Drafting is passive. Closing is active. A great AI quoting agent isn’t just generating PDFs—it’s helping you win business.
That starts with how it handles the initial request. Imagine an RFQ comes in from a customer you haven’t worked with before. It’s a bit messy—attached specs, a vague delivery timeline, and no clear contact info. A good AI agent reads the file, pulls out the key details, identifies what’s missing, and drafts a clear, professional reply asking for what it needs to move forward.
But it doesn’t stop there. It builds the quote based on your pricing logic and past jobs. It formats it in a way that looks sharp and professional, just like a seasoned salesperson would. Then it sends it—promptly—with a friendly message that sounds like it came from your team. It even knows to follow up a few days later if the customer doesn’t respond.
That follow-up step is key. It’s where most quoting systems fall flat. In reality, a big chunk of deals are won simply because someone followed up at the right time. With an AI agent doing that for every quote you send, you increase your odds across the board. Even if your team is swamped, the agent is still working, still nudging, still moving opportunities forward.
Let’s say a fabrication shop in Texas uses an AI agent that handles this entire loop. They’re sending out 2x more quotes than before. Their win rate climbs 15%. Why? Because they’re quoting faster and staying in front of more customers without extra headcount. It’s not that they hired better people. They deployed a better process—one that doesn’t rely on people remembering to follow up.
You Step In Only When It Matters
Of course, not every quote is simple. Some are complex. Some involve special materials, tight tolerances, or odd delivery requirements. A strong AI agent knows when to flag you in. It’s smart enough to recognize when it’s out of its depth—and that’s a good thing.
You don’t want an AI pretending to know your margins on a tricky custom assembly. You want it to say, “Hey, you should look at this one.” That’s the ideal relationship: the agent handles 80-90% of the volume, and you or your team handle the edge cases. You focus on the quotes that truly need your judgment. The rest? Done and gone.
This model is a huge mindset shift. Instead of trying to automate everything, you’re automating the right things—the repeatable, the straightforward, the follow-ups that often fall through the cracks. You stay in control where it counts.
Picture a parts supplier that used to review every RFQ by hand. After deploying a quoting AI, they reduced manual review by 70%. Now their sales lead only looks at quotes over a certain dollar threshold or ones flagged as complex. That means more focus, fewer mistakes, and more energy spent on the deals that matter most.
Scale Without Hiring and Training
Hiring great quoting talent is hard. Training them takes time. And even once you have them, you’re limited by their capacity. People can only handle so much. They get tired. They go on vacation. They burn out.
An AI quoting agent doesn’t. It can handle hundreds of quotes a week, across time zones, across product lines, across customer types. It doesn’t get overwhelmed. It doesn’t need hand-holding. And when your business grows, you don’t need to immediately hire to keep up.
This is especially powerful for businesses with seasonal swings or unpredictable demand. If quoting volume spikes during a busy quarter, the AI scales with it. If it slows down, no problem—you’re not carrying overhead you don’t need.
A hypothetical CNC machining business in Michigan saw this firsthand. They were growing fast but couldn’t keep up with quoting. Instead of hiring two more estimators, they rolled out an AI agent. Within six weeks, it was handling 85% of incoming RFQs on its own. They never hired—and still grew revenue 20% year-over-year.
That’s what makes this technology so valuable. It doesn’t just replace effort. It unlocks capacity.
What Makes a Great AI Quoting Agent?
If you’re thinking about trying one of these tools, look for seven essential features:
1. It reads and understands real RFQs.
A strong quoting agent can handle the kind of messy, unstructured requests manufacturers deal with every day—spreadsheets, PDFs with notes in the margins, emails with half the details buried in attachments. It needs to recognize part numbers, quantities, delivery dates, and customer requirements across all these formats. This ability to quickly digest and organize RFQ data saves your team hours of sorting and rework.
2. It builds complete, accurate quotes.
Your quoting agent shouldn’t just plug numbers into a form. It should understand your pricing logic, factor in lead times, material costs, and build quotes that reflect your real margins and production capabilities. It should also apply standard terms, discounts, and delivery estimates that are accurate and consistent with how your business operates.
3. It writes like a human.
A great agent doesn’t send robotic emails that feel like they came from a machine. It should write in your voice, using language that matches how your business communicates with customers. When the quote goes out, it should read like it came from your most professional salesperson—clear, friendly, and confident.
4. It follows up automatically.
Most sales are lost not because the price was wrong—but because no one followed up. Your AI quoting agent should keep track of every quote it sends and follow up regularly until it gets a response. Whether it’s a quick nudge or a reminder with revised terms, consistent follow-up helps turn more quotes into closed deals without manual effort.
5. It knows when to ask for help.
Not every job is straightforward. When an RFQ includes complex specs, unusual materials, or vague requests, the quoting agent should flag it for human review. Instead of trying to fake it, it should bring you or your team in to handle the edge cases—so you stay in control where it matters most.
6. It tracks performance.
You should be able to see how many quotes were sent, how many converted into orders, how long it took to respond, and where potential deals are getting stuck. A great quoting agent gives you clear, actionable insights so you can identify bottlenecks, improve processes, and make smarter decisions over time.
7. It gets better over time.
The more your agent quotes, the smarter it should get. By learning from past jobs—what won, what lost, how long things took—it can begin to fine-tune pricing suggestions, better detect complex jobs, and improve how it responds. This continuous learning turns a good quoting agent into a great one—one that keeps delivering more value as it goes.
It’s not about replacing people. It’s about putting a reliable, tireless digital teammate on your quoting team—one that helps you grow without growing your payroll.
3 Clear, Practical Takeaways You Can Use Now
- If quoting is slowing down your growth, an AI agent can fix that without hiring. Start with one product line or customer segment. Let the agent handle the easy stuff and measure the lift.
- Speed + follow-up = more closed deals. Most businesses don’t lose on price—they lose on response time. With an AI agent quoting within hours and following up automatically, you’ll win more often.
- Your quoting process is a revenue engine. Treat it like one. Every RFQ is a chance to grow. The right AI agent doesn’t just help you respond faster—it helps you close smarter, scale easier, and build a quoting machine that runs while you sleep.
Questions Manufacturers Ask Before Using an AI Quoting Agent
Will an AI quoting agent work with the way we currently receive RFQs?
Yes—if you choose the right tool. A good quoting agent can handle RFQs in all the formats you already deal with: spreadsheets, PDFs, emails, customer portals, and even scanned documents. It’s designed to adapt to your existing workflow, not force you to change how customers send requests.
How accurate are the quotes it generates?
Very accurate—if it’s trained on your pricing rules, margins, and delivery standards. The best quoting agents use your actual business logic to generate quotes. They’re not making guesses—they’re applying the same logic your team would use, just faster and without fatigue.
Will it still involve my team when needed?
Absolutely. The goal isn’t to replace your team—it’s to take repetitive quoting work off their plate. When an RFQ is complex, unclear, or unusual, the agent flags it and prompts someone to step in. You stay in control, especially when judgment or technical expertise is needed.
How does it help with sales follow-up?
Once the quote is sent, the AI agent can follow up with the customer automatically—on your behalf. That might include a friendly reminder, a revised quote, or a response to a question. It keeps the deal moving without your team having to remember to check in manually.
Can it really replace hiring a new quoting person?
In many cases, yes. A well-trained AI agent can handle the quoting volume of a full-time team member, without the overhead of hiring, training, or managing burnout. It also scales instantly—handling ten RFQs or a hundred without missing a beat. That’s a game-changer for growing businesses.