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Reveel's Omnicarrier Decision Intelligence to Optimize Shipping Costs Before Invoices Arrive

This AI-native capability enables shippers to plan and manage their entire carrier network in real-time, at the package level, without relying on blended averages, static reports, or a carrier’s own numbers.

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Reveel launched Omnicarrier Decision Intelligence (ODI), an AI-native capability that enables shippers to plan and manage their entire carrier network in real-time, at the package level, without relying on blended averages, static reports, or a carrier’s own numbers.

“For years, carrier strategy was relatively straightforward. Most parcel shippers worked with the same carrier, across three-year agreement cycles, with one or two price increases a year. That market is gone. The major carriers now rarely want all of a brand’s shipping business, which is why across parcel, LTL, truckload, and international we see an endless stream of mid-year price increases, surcharge repricing, converging modes, and an explosion of alternative carriers in an ecosystem that is more complex and less predictable than ever,” says Josh Dunham, co-founder and CEO at Reveel. “Omnicarrier Decision Intelligence ensures that as carriers evolve, the shipper evolves with them. With legacy operating models, shippers could only find out what a carrier agreement cost them after the invoice arrived. ODI changes the sequence entirely. Using modeling and simulation to optimize shipments across all carriers, it plans and manages the network in real time, at the package level, and across every carrier a shipper runs, before the cost ever lands on an invoice.”

Key takeaways:

·        The AI-powered unified analytics suite is now enhanced with interactive AI-powered KPI dashboards, configurable alerts, actionable insights, customizable personalization, all fully integrated to IQ, Reveel's conversational AI.

·        The Carrier Mix Modeler lets shippers model the ideal carrier network for all parcel shipments in real-time, matching each and every package with the right carrier.

·        Costs are planned and managed in real-time in a constant feedback loop, enabling optimal decision making before shipments are made – not after contracts are signed, carrier invoices are received, and shipping expenditures impact profit and loss.

·        ODI spans Reveel’s three operating pillars:

Plan (strategy and sourcing): models any carrier rate proposal or diversification scenario against a shipper’s actual package level shipment history, computes the full financial impact of every proposed term before signature, and models the cost impact of a GRI or surcharge restructuring within minutes, instead of weeks.

Manage (analytics and insights): unifies spend and performance data across every carrier, account, and location into one continuously updated view, and surfaces surcharge changes and billing anomalies within the same billing cycle as they occur, not after.

Govern (audit, monitor and report): which oversees a shipper’s complete shipping program. Every invoice is validated against contracted terms within the billing cycle through Reveel’s Parcel Audit & Recovery solution, while the platform’s Freight Audit & Payment capabilities extend that same audit-grade precision to every mode of transportation. 

·        Central to ODI’s Manage capability is Reveel IQ, an AI shipping analyst purpose-built on shipping and carrier domain expertise. Rather than adding another alert feed for a team to interpret, users can ask Reveel IQ a question using natural language and it translates carrier data into ranked, dollar-quantified recommendations that can be acted on immediately. 

·        The platform’s Automated Financial Grade Reporting function  delivers an audit trail, giving the real number the finance and compliance teams require.

·        Reveel is also introducing a Model Context Protocol (MCP) Connector, enabling AI agents to discover and invoke Reveel services directly. The connector extends the same governed, permissioned access to any AI agent acting on their behalf, all in accordance with the National Institute of Standards and Technology (NIST) AI Risk Management Framework.

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