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Why freight quotes take so long, and how to speed them up

Yash Singh · 16 Oct 2026 · 2 min read

A customer sends an email at 10 in the morning. They need a 32 foot truck from Chakan to Zaheerabad on Thursday, and they want a quote by the end of the day. Simple enough.

Now look at what happens next on most RFQ desks.

One request, many steps

1. Someone reads the email and works out what is needed: vehicle type, weight, pickup time, any special handling. Often a detail is missing, so they write back and ask.
2. They decide which transporters to ask, usually from memory or an Excel sheet.
3. They send the requirement out, one email or WhatsApp message at a time.
4. Rates come back over the next few hours in different formats. Some in the email, some in a PDF, some as a voice note.
5. They put the rates side by side, push back on the high ones, and wait again.
6. They add their margin and send the customer a quote.
7. If the customer agrees, they confirm the transporter, collect vehicle and driver details, and enter everything into the ERP or TMS.

None of these steps is hard. But almost every one involves waiting for someone, and the desk is doing this for dozens of requests at once. A request that arrives after 6 pm usually waits until the next morning.

Why another app usually does not help

Many companies have tried freight bidding platforms. The idea makes sense: put all your transporters on one portal and let them bid. In practice, transporters keep replying on WhatsApp and email, because that is how they already work. The portal becomes one more place to check.

One operations head told us they had tried several bidding apps, and none of them stuck. We took a simple lesson from that. Do not ask people to change where they work. Do the work where it already happens.

What an AI agent does instead

An RFQ agent works inside the same email and WhatsApp threads your team already uses. When a request comes in, it:

• reads it, pulls out every detail, and asks the customer about anything missing
• sends the requirement to the right transporters for that lane
• reads their replies in whatever format they arrive, and puts the rates side by side
• drafts the quote using your pricing rules
• once the load is confirmed, collects vehicle and driver details and updates your ERP or TMS

Your team decides what needs their approval. In the beginning, that is usually everything. Over time, routine quotes on familiar lanes can go out on their own, while anything unusual still comes to a person.

The agent also does not stop at 6 pm. A request that lands at night is read, sent out and ready for review by the time the desk opens.

What this looks like in practice

At a 3PL in India, an agent took over the spot freight workflow over email: reading inquiries, collecting bids, keeping them up to date, awarding the load and collecting vehicle and driver details. Manual effort in that workflow fell by about 80%. Read the case study.

Want to see the difference side by side? Watch a human RFQ desk and an agent work the same inbox.

Keep reading

• Case study · 16 Oct 2026 · 2 min read

  How a 3PL cut manual work on spot freight by 80%

  Spot freight requests arrived by email from dozens of addresses. Here is what changed when an AI agent started handling them.

• Blog · 16 Oct 2026 · 3 min read

  AI agents for logistics, explained simply

  Everyone is talking about AI agents. Here is what one actually does in a logistics team, without the jargon.

No Horn: the autonomous back office for enterprise logistics. Write to yash@nohorn.in.