The Problem
The company runs one of the most time-sensitive distribution networks in consumer goods: live plants, with a peak shipping window of March through May when the entire year's revenue compresses into twelve weeks. The logistics team managing it was operating on BluJay — a cloud-migrated legacy TMS that covered outbound planning and visibility but left critical gaps everywhere else. Carrier scorecards did not exist. Fuel surcharge updates were cumbersome. Historical analysis was unavailable for scheduling decisions. Some planning capabilities happened entirely outside BluJay. Procurement ran manually through Excel benchmarking. Freight bill and audit was 100% manual for all inbound and outbound shipments.
The audit gap was structural. With no carrier scorecard, no automated accessorial matching, and no connection between contracted rates and actual invoices, the team had no systematic way to catch overbillings before payment. The manual audit process consumed staff time that should have gone to route optimization and carrier management — the work that actually moved the needle on cost. With no configurable rate management and no real-time costing capability, the finance team had no way to provision freight spend or generate accurate accruals until invoices arrived, weeks after shipments had occurred.
The BluJay license ran through February 2026. The company needed to evaluate and deploy a replacement in phases around a hard constraint: no functional resources could be committed during March through May, the peak window when the business ran at full capacity. The implementation had to fit that calendar without creating overlapping licenses or operational disruption at exactly the moment the business could least afford it. The deployment plan had to be phased not by IT complexity, but by agricultural seasonality.
The evaluation assessed alternatives against a specific requirement set: rate management integrated with execution, procurement automation with SONAR benchmarking integration, automated freight audit with 4-way match capability, and TMS coverage across all modes — all on one platform, at a comparable total cost of ownership to BluJay, with low IT effort due to the cloud-native architecture.
What Freehand Did
Freehand deployed in four sequential phases timed around the agricultural calendar. Phase 1 activated the Rate Manager Agent and AI Procurement Analyst — digitizing all carrier contracts into a single live rate repository and launching automated procurement events integrated with SONAR for live market benchmarking. The procurement capability went live before the March peak season, giving the logistics team AI-assisted carrier selection and cost visibility for the first time in advance of the busiest twelve weeks of the year. The Procurement Analyst's scenario modeling compared carriers on cost, performance, and lane coverage simultaneously — replacing the Excel benchmarking that had made every sourcing event a manual project.
Phase 2 deployed the Audit Agent and the Invoice Ingestion Agent on top of the rate repository Phase 1 had established. Because rate data was already digitized and structured, the audit layer activated without a separate data-gathering exercise. The 4-way match — invoice against contracted rate, against accessorial schedule, against actual shipment weight, and against execution data — replaced the manual invoice review that had consumed staff hours for every shipment. Duplicate detection and overbill identification run continuously. The GL Coding Agent automates account assignment at the line level, producing accurate accruals in real time rather than estimates assembled after invoice receipt.
Phase 3 brought Pando TMS live for outbound planning and visibility — integrated with Sage ERP and p44 for real-time tracking. The BluJay license ended without overlap. Carrier integrations migrated to Freehand's carrier network without the EDI maintenance burden the prior system had required. Dynamic routing replaced the static routing guide that had limited the team's ability to respond to demand shifts during peak. The Collaboration Agent manages carrier performance scorecards and handles exception communication — the manual carrier follow-up that had accumulated during peak season now runs autonomously.
The Spend Intelligence Agent closes the loop: freight spend by carrier, mode, lane, and cost center is visible in real time, enabling the finance team to provision spend before invoices arrive and the procurement team to identify underperforming lanes before the next sourcing cycle. An additional nursery network acquired during the deployment period was incorporated into Phase 4 without a separate implementation. The company that had run logistics on a patchwork of tools, manual processes, and tribal knowledge now operates on a single AI platform — procurement to audit to payment — with the same intelligence that benchmarks carrier rates also catching the billing errors that erode them.
