Challenge

Arrive Logistics is a $2.35 billion, 1,700-employee brokerage and 3PL that moves tens of thousands of truckload shipments across North America every week. But behind the growth headlines lurked an operational tax:

Reps chased proofs-of-delivery (PODs), appointment confirmations and rate-con updates across email, phone, TMS and spreadsheets—often touching the same load nine times before it invoiced.
Average document cycle time stretched past 48 hours, pushing days-sales-outstanding higher and burning cash.
With turnover above industry norms, each new pod of brokers cost roughly $300 k/year in salary and training, yet margin per load kept slipping as service KPIs dipped below shippers’ 95 % OTIF targets.

Leadership could keep hiring—or re-think the workflow altogether.

Solution

Instead of more bodies, Arrive brought in Augie, Augment’s AI teammate designed for logistics. In one week Augie ingested two years of historical lane, carrier and SOP data, then embedded itself alongside brokers inside MercuryGate, CargoWise, Slack and Outlook.

Hands-off execution – Augie auto-logged status events, emailed milestone updates, filed PODs to the right load, and raised exceptions in a Slack “triage” channel before they became chargebacks.
Continuous learning loop – Every interaction (e.g., learning that Hector left and Ben is now the consignee contact) was written to a shared knowledge base, compounding accuracy and eliminating tribal knowledge loss.
Human-first design – Augie asked for help when workflows hit a policy edge case, mirroring a junior teammate rather than a rigid bot—a capability Arrive’s CEO Matt Pyatt highlighted in the launch announcement

Augie was effectively a 24/7 fifth wheel in every pod, shouldering the drudgery so brokers could focus on carrier negotiations and strategic bids.

Result

Twelve months after go-live, internal reporting showed transformative gains: