A field guide to freight quoting software in 2026

Freight forwarders evaluating quoting technology in 2026 meet a crowded market where most tools sound similar. Nearly every vendor now says “AI quoting”. The tools are genuinely different, though. They start from different places, solve different parts of the quoting problem, and most forwarders end up running several of them together.

This guide explains the five categories, what each one actually does, and how they combine. We build Nexcade, which sits in one of these categories, and we work alongside tools from the others every week. The aim here is an accurate map.

Why quoting is the hard part

A spot quote looks simple from the outside: a customer emails a request, the forwarder replies with a price. In practice the work spans several systems. Someone reads the request and extracts the shipment details. Someone finds rates: contract rate cards, airline and carrier platforms, broker desks, tariff sheets, or an email to an overseas agent when nothing else covers the lane. Someone assembles the legs (a main air or ocean leg, plus pickup, delivery, handling, and local charges that often live in different places), applies the house margin policy, and writes the quote. Someone records it in the TMS so it can be audited and converted into a booking if it wins.

Each software category below automates a different slice of that chain.

1. Rate platforms and booking marketplaces

Examples: cargo.one, WebCargo by Freightos.

These are two-sided platforms. Carriers distribute capacity and rates on them; forwarders search, compare, and book. cargo.one describes itself as an AI-native operating system for air and ocean, with rate management, e-booking, and AI quoting built on its rate database. WebCargo describes an end-to-end air cargo platform with rate management, pricing, quoting, booking, and sales tools across 300+ air carriers.

Their defining strength is the marketplace: live, bookable carrier capacity in one place. Their quoting features work outward from that database, plus rates the forwarder loads into the platform. They are strongest when the rates a forwarder needs live on, or in, the platform.

2. Rate management systems (RMS)

Examples: Freightify, CargoSphere, and the rate engines inside the platforms above.

An RMS centralises the forwarder’s own contracted rates: procurement, storage, cleaning, and distribution. Freightify describes an AI-powered rate management platform that centralises spot and contract rates and integrates with CargoWise and other TMS/ERP systems. CargoSphere, a WiseTech company, runs a neutral rate network for ocean rates and specialises in turning static carrier contracts into clean, queryable data.

An RMS answers the question “what are our rates?”. It depends on the rates being loaded and kept current, which is real ongoing work, and it typically serves pricing teams as the system the rest of the workflow queries.

3. TMS quoting modules

Example: CargoWise Quotations and One Off Quotes.

Most forwarders already quote inside their TMS to some degree. CargoWise users can create contract and spot quotes directly in the platform, and for many operations the one-off quote is the official record: the thing that gets audited, referenced, and converted into a booking when the customer accepts.

TMS modules are the system-of-record layer. They are where a quote should end up, whatever produced it. The manual work of gathering rates and assembling the quote still has to happen somewhere.

4. AI quote-workflow agents

Examples: Nexcade, and a growing field of specialised vendors.

This category starts from the inbox. Software agents read incoming requests, extract shipment details, gather rates from the sources the forwarder already uses (rate platforms, RMS, tariff sheets, portals, and email outreach when a rate is missing), assemble multi-leg quotes, apply the forwarder’s own pricing policy, and write the result back into the TMS. Nexcade runs this as a team of specialised agents covering triage, quotations, tenders and rate refresh, bookings, and analytics, with review gates so operators approve what matters.

The defining trait is that the workflow layer holds no rates of its own. It reads the forwarder’s existing sources and writes into the forwarder’s existing systems. Its value depends on covering the messy edges: requests that span several rate sources, lanes where a rate has to be chased by email, exceptions, and the writeback that keeps the TMS the source of truth.

5. In-house builds

Examples: C.H. Robinson’s AI agent fleet, DSV’s quote-and-rate platform.

The largest logistics companies build their own. C.H. Robinson reports hundreds of connected AI agents in production, including quoting agents handling requests that arrive by email. DSV presented an AI-supported email quoting workflow at its 2026 Capital Markets Day, built on its in-house platforms. DP World has said publicly that it is developing in-house quoting tools while using cargo.one to aggregate airline rates into them.

Building works at a certain scale of engineering investment, and it still tends to buy layers (rate aggregation, for instance) where a market already exists. We cover the trade-offs in a separate guide.

How forwarders actually combine them

The categories stack. A typical modern setup: carrier rates arrive through a rate platform and an RMS; the TMS stays the system of record; a workflow layer (bought or built) connects the inbox to the rates to the TMS. The DP World example above is this pattern at global scale: build the tool, buy the rate layer.

The practical evaluation question is rarely “which one tool?”. It is “which layers do we already have, which are weakest, and what connects them?”. For closer looks at individual pairings, see Nexcade and cargo.one and Nexcade and rate management systems.