Every RFQ you’ve ever received. Every quote you’ve ever sent. Every negotiation thread with a carrier, every pricing exception, every “hey can you do better?” reply. It’s all there—hundreds, thousands of emails over the years—silently recording how your business thinks about price.
What if you could turn that history into a living, learning system? What if, instead of retyping the same quotes or chasing old files, your inbox started working for you?
That’s the promise of AI-powered quoting. And it starts with what you already have.
Rate sheets are static. TMS exports are often incomplete. Pricing templates can’t explain why you shaved $50 off that LAX–ORD shipment last December.
But your inbox? It remembers. It remembers how you priced that rush shipment with white-glove service. It remembers how you structured the quote for that pharma client who always asks for packaging details. It remembers how you responded to that global account manager’s last-minute margin edit.
The inbox is where real-world pricing decisions happen—not in clean, structured databases, but in messy, human context. And that’s exactly what makes it so powerful when training AI.
When you feed your AI model with past emails and quote replies, you’re not just training it on numbers—you’re teaching it judgment. Nuance. Voice. Style. You're giving it the exact same learning curve your best operators spent years developing—instantly.
The process isn’t magic. It’s methodical.
Modern AI quoting tools can now ingest and interpret past emails—extracting:
That data becomes your model. It learns how you quote different clients. It understands what pricing looks like for high-priority lanes. It starts to predict what you’re likely to quote next—and how.
And once it learns, it doesn’t just sit quietly. It starts generating draft quote replies in real time. The moment a new RFQ hits your inbox, the system uses your own historical logic to build a first draft—customized, context-aware, and ready to send.
You don’t have to upload price lists. You don’t have to “teach” it manually. You already have what it needs: a goldmine of decisions sitting in your Gmail or Outlook account.
Let’s be clear: this isn’t about letting AI run wild with customer communications. You’re still in charge. You review the draft, tweak what’s needed, and hit send. The difference is, you’re no longer starting from a blank page.
Think of it like hiring an assistant who’s read every quote you’ve ever sent and never forgets a thing. Someone who watches how you operate, and makes your life 10x faster without making you feel replaced.
That’s what AI trained on your inbox becomes: an operational accelerator that quotes like you—only faster.
When your AI is trained on your pricing history, you don’t just move faster—you move smarter.
And perhaps most importantly, you finally unlock scalability without sacrifice. You stop being dependent on the two senior ops leads who “know how it’s done,” and start building a system where the knowledge lives in your workflow—not in someone’s head.
The freight industry has no shortage of data. But most of it sits in the wrong place—hidden in email archives, siloed in personal inboxes, lost in old quote templates.
What if you could take all that invisible knowledge and put it to work?
What if your AI could learn from every pricing move you’ve ever made—and use it to win the next 1,000 shipments?
You don’t need a new platform. You don’t need a data science team. You just need to start with what you already have.
Because in freight, the fastest path to quoting smarter isn’t building from scratch. It’s unlocking the goldmine sitting in plain sight.
Your inbox knows how you win freight.
Now it’s time to teach your AI.
