Freight Analytics transforms complex shipment data into structured intelligence — explaining why costs move, aligning the right capacity, and governing execution with defensible precision.
Reduction in freight costs can drive a 6–15% increase in net profit for large shippers — making this one of the highest-leverage financial levers available.
Average annual freight leakage for shippers with $50M–$100M freight budgets — driven by audit gaps, planning inefficiency, and undetected accessorial overcharges.
Average freight rate volatility driven by market conditions, capacity shifts, and seasonality — the signal that makes cost explanation so difficult without structured intelligence.
Freight Analytics is not a dashboard. It is a unified intelligence system — where cost analysis, capacity alignment, and audit governance reinforce each other to produce conclusions that are defensible at every level of your organization.
Each domain feeds the next. FLX explains cost. RPX aligns capacity to the right profile. FIX verifies execution and closes the loop — so every improvement is validated, traceable, and durable.
From data to decision-grade insight
Explains why freight costs move — separating market forces, planning decisions, network structure, service choices, and execution outcomes into clear, attributable categories.
Right carrier, right lane, right fit
Matches recurring freight with asset-based carriers whose operating profile fits the shipment — not the lowest bid. Covers truckload (RPX 100), air cargo (RPX Air), and ocean (RPX Sea).
ISA methodology, AI-powered enforcement
Closes the loop by verifying freight charges and execution accuracy using an ISA-guided audit framework — linking cost discrepancies back to root causes, not just flagging anomalies.
FLX processes freight through a structured, multi-layer framework — so every cost conclusion is attributable, explainable, and defensible to finance, procurement, and executive leadership.
Most systems store freight as invoices and transactions. We model it as a semantic network — linking shipments, lanes, service levels, constraints, and cost drivers into a coherent, queryable structure that mirrors how freight is actually priced and executed.
Standard RAG models infer meaning from documents — and inherit every inconsistency in them. Freight Analytics engineers context directly into the data layer before AI is applied, so the system reasons from structured freight reality rather than probabilistic inference over fragmented records.
FIX doesn't just audit outcomes — it validates them against operational, contractual, and governance boundaries. This means AI learns from verified decisions, not raw repetition. The result is intelligence that improves over time without amplifying historical inefficiencies.
RPX organizes capacity around repeat lanes and consistent volumes, allowing shippers to align long-term carrier fit with how freight actually moves. Not lowest-bid tendering. Not load boards. Structural alignment that delivers lower costs through efficiency, not negotiation leverage.
Internal analytics optimize for operational visibility but collapse under financial scrutiny. Freight Analytics produces conclusions that are traceable to specific cost drivers, attributable to specific decisions, and defensible in front of auditors, CFOs, and board-level review.
Freight Analytics integrates external capacity signals from actual trucking fleets, airlines, and shipping lines — not broker-derived indices. This gives shippers a benchmark grounded in real operating economics, not intermediated market averages that obscure true cost structure.
"For Fortune 500 shippers, freight spend often rivals net profit. A 10% reduction in freight costs can drive a 6–15% increase in net profit."
Industry benchmark — Freight Analytics research basis
This makes freight optimization one of the highest-leverage financial opportunities available to a supply chain organization — and the one most consistently underinvested in due to lack of clear, defensible analysis.
Based on industry benchmarks. Actual results vary by shipper profile and network complexity.
Five sequential steps form the analytical spine of FLX — each building on the last to produce conclusions grounded in your freight reality, not generic benchmarks.
Shipments organized by mode, lane, equipment, service requirement, and operating pattern into a coherent freight network model.
Routing decisions, delivery windows, procurement policies, and carrier engagement history embedded within each shipment's analytical record.
External capacity dynamics, seasonal volatility, and equipment availability evaluated against the shipper's specific freight profile — not generic indices.
Distribution footprint, shipment density, consolidation opportunities, and dwell time assessed against the actual network that exists.
Multi-layered cost framework produces transparent, traceable conclusions — not just variances, but explanations that support governance and executive review.
Freight Analytics is in active development with select shipper partners. If your organization manages significant freight spend and needs defensible, explainable cost intelligence — we'd like to talk.