By Luis Lopez, AI transportation consultant, CEO of Go Hub.io Holdings Corp and subsidiaries, and host of the Freight Guru Podcast
Drayage quotes look simple until the invoice arrives. The base rate from the port to the warehouse is usually the easy part. The hard part is everything that might happen around it: chassis days, prepulls, storage at the yard, waiting time at the terminal, overweight handling, and hazmat requirements. A quote that ignores those possibilities is not really a quote. It is a starting number.
Software that uses AI to build drayage quotes tries to account for the whole move, not just the line-haul miles. Here is how these tools work, what data they rely on, and where human judgment still has to step in.
The Core Inputs
Every drayage quote starts with a set of facts about the move. The better these inputs are, the better the quote:
- Terminal or port of origin: Different terminals have different congestion patterns, appointment rules and turn times.
- Delivery location: Usually a zip code or full address, which determines distance, tolls and local access issues.
- Container size and type: 20 ft, 40 ft, 40 ft high cube or 45 ft, and whether it is a standard dry box or special equipment.
- Cargo weight: Heavy containers may require special chassis or permits and affect which trucks can do the move.
- Live unload or drop: A live unload ties up the driver and truck; a drop needs a chassis to stay with the container.
- Chassis source: Whether the chassis comes from a pool, the carrier or another provider.
- Hazmat and overweight flags: Both change which carriers can take the load and what extra charges apply.
Many quoting errors start with missing or wrong inputs. A tool that asks the right questions upfront, or extracts them from the shipper’s email and documents, prevents a lot of rework. For background on chassis arrangements, see our post on chassis fees, splits and pools.
Learning From Historical Rates
The base rate usually comes from history. Software looks at past moves from the same terminal to similar delivery areas, adjusting for container size, weight, and timing. With enough data, it can estimate a reasonable base rate for a lane even if that exact address has never been served before.
Historical data has blind spots. Rates from a slow season may not reflect a busy one, and a lane with only a handful of past moves gives a shaky estimate. Good tools show how much data supports each estimate, so the person quoting knows when to trust it and when to check with carriers.
Predicting Accessorials
This is where AI adds the most value. Accessorial charges are often what turns a good quote into an unhappy customer. Software can estimate the probability that a given move will incur:
- Chassis days beyond what is included, based on typical unload times at that consignee and the live-versus-drop choice.
- Prepull charges, when containers need to be pulled from the terminal early to avoid storage or meet a delivery appointment.
- Yard storage after a prepull, while the container waits for its delivery slot.
- Waiting time at the terminal or at the customer’s dock.
- Split or extra trips when a chassis must be picked up or returned at a different location.
Rather than burying these charges in fine print, a well-designed quote shows them as likely or possible, with the conditions that trigger them. Our article on how to audit a drayage invoice walks through what each of these charges means on the bill.
Terminal Congestion Signals
Terminal conditions change quickly. When a terminal is congested, appointments are harder to get, wait times grow, and prepulls become more common. Pricing software can watch signals such as appointment availability, recent turn times reported by drivers, and vessel arrival schedules.
When these signals point to congestion, the tool can adjust accessorial probabilities or flag the quote for review. For more on how congestion affects planning, see our post on port congestion and shipper planning.
Fuel Surcharge
Most drayage quotes include a fuel surcharge that moves with a published fuel price index. Quoting software typically applies the current surcharge schedule automatically and notes that the final surcharge may change by the time the move happens. That note matters, since quotes are often accepted days or weeks before the container is available.
Explaining the Quote
A number on its own is hard to trust. The best quoting tools explain how they arrived at the price:
- The base rate and what it covers.
- Included free time for chassis and waiting.
- Likely accessorials and the conditions that would trigger them.
- Assumptions about weight, appointment availability and live or drop delivery.
- How long the quote is valid.
As an AI transportation consultant, the first thing I look at when reviewing a quoting tool is whether a customer service rep could read its output to a shipper and answer their follow-up questions. If the logic is hidden, nobody can defend the price when the invoice comes in higher than expected.
Human Review for Unusual Moves
Some moves should always get a person’s attention before a quote goes out:
- Overweight containers that may need special chassis or permits.
- Hazmat loads that require certified drivers and specific documentation.
- Out-of-gauge cargo on flat racks or open tops, which usually needs special handling and permits.
- Deliveries to sites with tight access, residential streets or unusual hours.
- Lanes with little historical data.
- Urgent moves where the container is already near the end of its free time.
Software can identify these cases and route them to an experienced pricer, rather than producing a confident number that turns out to be wrong.
Limits of AI Drayage Pricing
AI pricing is a tool, not a guarantee. Keep these limits in mind:
- Historical rates lag behind sudden market changes.
- Accessorial predictions are probabilities. A move can still incur charges the model rated unlikely.
- Terminal rules, free time and fees can change, and software may not reflect changes immediately.
- Bad inputs, such as a wrong weight or missing hazmat flag, produce bad quotes no matter how good the model is.
- Carrier capacity on a given day can override any calculated price.
Set clear guardrails, such as minimum margins and maximum discounts, and review quote accuracy against actual invoices regularly. That feedback loop is what makes the tool better over time.
The Bottom Line
Good drayage pricing is about more than miles. Software that combines terminal data, delivery details, historical rates and accessorial probabilities can produce quotes that look much closer to the final invoice. Paired with clear explanations and human review for unusual moves, it helps shippers budget accurately and helps drayage providers avoid underpricing risky loads.
For more conversations on freight and AI, subscribe to the Freight Guru Podcast.
About the author: Luis Lopez is a Miami-based AI transportation consultant and logistics entrepreneur, the CEO of Go Hub.io Holdings Corp and subsidiaries, and host of the Freight Guru Podcast.