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
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.
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.
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.
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.
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.
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
Week 1: Discovery — audit rate sheet formats from top carriers, map rate structures and surcharge taxonomy, define normalisation schema
Week 2–3: Build — rate extraction AI, normalisation engine, comparison interface, validity tracking
Week 4–5: Integration — email monitoring for rate updates, TMS/quoting system connection, rate expiry alerting
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
| Metric | Result | Context | Business Outcome |
|---|---|---|---|
| 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 |
From 3 days/month manual entry to automated ingestion
Pricing team focuses on strategy, not data entry
Down from 15–30 minutes of spreadsheet searching
Faster quote turnaround, more quotes per day
Rate validity tracking and expiry alerts prevent outdated pricing
Protect margins from rate update delays
From kickoff to production with initial carrier rate ingestion
Immediate value from first rate sheet batch
Works with your existing TMS
Direct integration with CargoWise, SAP TM, Oracle TMS, Microsoft Dynamics, and Descartes.
Rate Intelligence — Frequently Asked Questions
What is freight rate sheet intelligence?
Can it read rate sheets in any format?
How does rate normalisation work?
Does it integrate with our quoting system?
How quickly are new rate sheets reflected in the system?
How does this compare to Freightify or Cargorates.ai?
Can it detect rate anomalies and pricing errors?
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Works With
Ready to Automate Your Rate Intelligence?
Book a free audit. We'll show you exactly what we'd build for your operations.