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freight rate management AI

Carrier Rate Sheets That Read Themselves

AI that ingests rate sheets from any carrier in any format — PDF, Excel, CSV, email body — normalises all charges into a structured, searchable database, and gives your quoting team instant access to the best rate on every lane. No manual entry. No stale spreadsheets. Built on the same AI extraction engine deployed for Hellmann Worldwide Logistics.

Built For

Who Needs Rate Intelligence Automation

  • Freight forwarders managing rate sheets from 20+ carriers that arrive in different formats
  • Quoting teams spending 30+ minutes per quote searching for the right rate across multiple spreadsheets
  • Pricing managers who can't compare carrier rates by lane because data is trapped in PDFs and emails
  • Companies losing margin because rate updates aren't reflected in quoting systems fast enough

Before FreightMynd

Your rates live in 47 different spreadsheets and nobody knows which one is current

Carrier rate sheets arrive in every format imaginable: PDFs, Excel files with custom layouts, CSV exports, rate tables embedded in email bodies, and sometimes just a few lines of text with effective dates. Every carrier uses different terminology, different surcharge structures, and different validity periods. Your pricing team downloads these, manually transcribes them into your rate management system or master spreadsheet, and tries to keep track of which rates are current. When a quote request comes in, the quoting team searches across multiple files for the right rate on the right lane — a process that takes 15–30 minutes per quote and still sometimes uses stale rates because the latest update hasn't been entered yet.

Rate sheets arrive in 10+ different formats — PDF, Excel, CSV, email — each requiring manual reading and transcription into your system

Rate updates take 2–5 days to enter into your quoting system because someone has to manually transcribe them from carrier communications

Quoting teams spend 15–30 minutes per quote searching for the right rate across multiple spreadsheets and rate management tools

Stale rates in the quoting system cause margin erosion — quotes go out at old rates while carrier costs have already increased

No ability to compare rates across carriers by lane — data is siloed in carrier-specific formats that can't be easily cross-referenced

Surcharge structures vary by carrier — GRI, BAF, THC, EBS, LSS — making true cost comparison nearly impossible without manual calculation

What We Build

Rate Intelligence AI Capabilities

1

Multi-format rate sheet ingestion

AI reads rate sheets in any format: PDF rate tables, Excel files with custom layouts, CSV exports, email-embedded rate updates, and even scanned documents. The system identifies rate structures, surcharge components, validity periods, and lane applicability regardless of how the carrier formats them.

2

Automatic rate normalisation and structuring

Extracted rates are normalised into a consistent data model: base freight, surcharges broken down by type (BAF, THC, EBS, GRI, LSS, etc.), currency, container type, weight/volume breaks, validity period, and origin-destination pair. This normalisation makes cross-carrier comparison possible for the first time.

3

Carrier rate comparison by lane

With all rates normalised, your pricing team can instantly compare total cost across all carriers for any lane — including all surcharges, not just base freight. The system highlights the cheapest option, the most reliable option (from carrier performance data), and the best value-for-money option.

4

Rate validity tracking and expiry alerts

Every rate has a tracked validity period. The system alerts your pricing team before rates expire, prompts for carrier rate renewals, and flags quotes that reference expiring rates. No more discovering a rate has expired after a quote has been sent.

5

Quoting engine integration — instant rate access

Your quoting team accesses current rates directly from the normalised database — no spreadsheet searching. Quote building pulls the latest valid rate for the requested lane, adds applicable surcharges, applies your margin rules, and generates a quote in minutes rather than 30+ minutes.

6

Rate trend analysis and market intelligence

Historical rate data is analysed to show trends by lane, carrier, and season. Identify lanes where rates are rising, carriers that are getting more competitive, and seasonal patterns that affect pricing strategy. This intelligence informs both quoting and contract negotiation.

In Practice

Rate Intelligence Use Cases in Production

Auto-ingesting 40+ carrier rate sheets per month

A mid-size forwarder receives rate updates from 40+ carriers monthly in various formats. Previously, a pricing analyst spent 3 days per month manually entering rate updates. With rate sheet intelligence, carrier communications are processed automatically — rates are extracted, normalised, and available in the quoting system within hours of receipt, not days.

Instant cross-carrier rate comparison for quoting

When a quote request comes in for a Shanghai–Rotterdam FCL, the system instantly shows all-in rates from every carrier with valid pricing on that lane — including base freight, all surcharges, and transit time. What previously took 30 minutes of spreadsheet searching takes 30 seconds.

Rate expiry prevention and automatic renewal prompts

The system identified that 15 carrier rate agreements were expiring within the next 30 days — several of which were being actively used in open quotes. Automatic alerts triggered renewal requests to carriers and flagged affected quotes for rate validation, preventing margin erosion from expired rates.

Implementation

How We Deploy Rate Intelligence AI

Timeline: 4–6 weeks from kickoff to production

1

Week 1: Discovery — audit rate sheet formats from top carriers, map rate structures and surcharge taxonomy, define normalisation schema

2

Week 2–3: Build — rate extraction AI, normalisation engine, comparison interface, validity tracking

3

Week 4–5: Integration — email monitoring for rate updates, TMS/quoting system connection, rate expiry alerting

4

Week 6: UAT — validate extraction accuracy across carrier formats, calibrate surcharge classification, production deployment

Results

Measurable Impact

95%

Reduction in rate entry time

<1 min

Rate lookup time per quote

0

Quotes sent with stale rates

4–6 wk

Deployment timeline

Reduction in rate entry time 95%

From 3 days/month manual entry to automated ingestion

Pricing team focuses on strategy, not data entry

Rate lookup time per quote <1 min

Down from 15–30 minutes of spreadsheet searching

Faster quote turnaround, more quotes per day

Quotes sent with stale rates 0

Rate validity tracking and expiry alerts prevent outdated pricing

Protect margins from rate update delays

Deployment timeline 4–6 wk

From kickoff to production with initial carrier rate ingestion

Immediate value from first rate sheet batch

Tech Stack: PythonLangGraphOpenAI GPT-4oAzure Document IntelligencePostgreSQLn8n
Integrations: CargoWise One (Rate module)SAP Transportation ManagementRate management platformsMicrosoft Outlook / Gmail (rate email monitoring)Quoting systems

Works with your existing TMS

Direct integration with CargoWise, SAP TM, Oracle TMS, Microsoft Dynamics, and Descartes.

View Integrations

Rate Intelligence — Frequently Asked Questions

What is freight rate sheet intelligence?
Rate sheet intelligence uses AI to automatically read, extract, and normalise carrier rate sheets in any format (PDF, Excel, email) into a structured, searchable database. Instead of manual rate entry, your pricing team gets instant access to normalised, comparable rates across all carriers by lane — always up-to-date.
Can it read rate sheets in any format?
Yes. The AI handles PDF rate tables, Excel files with custom layouts, CSV exports, email-embedded rate updates, and scanned documents. Each carrier can use their own format — the system learns the structure and extracts rates regardless of layout.
How does rate normalisation work?
Every carrier structures rates differently — different surcharge names, different bundling, different units. Normalisation maps all carrier-specific terminology to a standard taxonomy: base freight, BAF, THC, EBS, GRI, LSS, etc. This makes true cross-carrier cost comparison possible by ensuring apples-to-apples comparison on every lane.
Does it integrate with our quoting system?
Yes. Normalised rates feed directly into your quoting workflow. When building a quote, the system pulls the latest valid rate for the requested lane, adds applicable surcharges, and applies your margin rules. Integration works with CargoWise rate module, SAP TM, and custom quoting systems.
How quickly are new rate sheets reflected in the system?
Rate sheets are processed within minutes to hours of receipt, depending on format complexity. Email-monitored rate updates are ingested automatically as they arrive. Compare this to the 2–5 day manual entry cycle in most operations.
How does this compare to Freightify or Cargorates.ai?
Freightify and Cargorates.ai are SaaS rate management platforms with their own UI and workflow. FreightMynd builds rate intelligence that integrates directly into your existing quoting workflow and TMS — you don't adopt a new platform. Rates are normalised and available wherever your team builds quotes, with cross-carrier comparison built into your existing process.
Can it detect rate anomalies and pricing errors?
Yes. The system flags anomalies during rate ingestion: rates significantly higher or lower than historical averages for the same lane, missing surcharge components, incorrect currency codes, or rates outside expected ranges. This prevents pricing errors from entering your quoting system and protects margins.

Ready to Automate Your Rate Intelligence?

Book a free audit. We'll show you exactly what we'd build for your operations.