Logistics Technology
Average shipping cost reduction delivered to client accounts
More client accounts analysable per analyst per week
About
ShipSigma helps high-volume UPS and FedEx shippers cut parcel costs through invoice auditing, rate analysis, and carrier negotiation. As their client base and shipment volume scaled, the manual analyst workflow behind each savings assessment became the bottleneck. We built the data science layer that automates rate analysis and route-level cost modelling behind their platform.
Industry
Logistics Technology
Company size
10 – 50 employees
Founded
2018
The Company
A fast-growing logistics-tech company outgrowing its own analyst bench
ShipSigma is an Indianapolis-based logistics technology company that helps high-volume parcel shippers reduce UPS and FedEx spend through invoice auditing, rate benchmarking, and carrier contract negotiation. Growth had been strong — a multi-year run on the Inc. 5000 fastest-growing companies list — and every new client meant another parcel invoice history to audit and another rate structure to model.
Each savings assessment required an analyst to manually parse carrier invoices, benchmark rates against comparable shippers, and identify accessorial charges and surcharges the client was paying that they didn't need to be.
The challenge
Manual rate analysis capped how fast the business could grow
A single client rate-and-route assessment could take an analyst the better part of two months from data intake to signed recommendation, most of it spent manually reconciling invoice line items against carrier rate cards and service-level agreements.
As deal volume grew, the analyst bench became the constraint on revenue growth rather than sales pipeline — a good problem to have, but one that put a hard ceiling on how many client accounts the business could onboard in a given quarter.
The Solution
An automated rate-modelling and route-cost engine
We built a parcel invoice parsing pipeline that ingests raw carrier billing data and automatically classifies every line item — base rate, fuel surcharge, accessorial, dimensional-weight adjustment — then benchmarks it against a rate library built from comparable shipper profiles. An OR-Tools-based route and service-tier optimiser layers on top, modelling the cost impact of shifting specific shipment profiles between carrier services or zones.
The output is a ranked list of savings opportunities with the dollar impact of each, replacing what used to be a manually assembled spreadsheet with a system that regenerates the full assessment automatically as new invoice data arrives.
The Results
From an eight-week bottleneck to a same-week turnaround
Time to first savings assessment for a new client fell from roughly eight weeks to three days, and each analyst could carry roughly four times the client volume without a corresponding increase in headcount. Clients moved through ShipSigma's own onboarding pipeline faster as a direct result.
The underlying savings delivered to client accounts held at an average of 25% off baseline shipping spend — the automation did not trade accuracy for speed, it removed the manual bottleneck standing between analysis and delivery.
We didn't build this to replace our analysts' judgment on a negotiation — we built it so they stop spending their time reconciling invoice line items and start spending it on the conversations that actually move a deal.
Head of Analytics, ShipSigma
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