The Problem
The company's marine propulsion division manufactures marine propulsion systems — engines, controls, and rigging — for recreational and commercial boats globally. With manufacturing facilities across the US and global distribution reaching over 100 countries, the freight procurement function managed a complex multi-modal network: ocean containers for international finished goods and component imports, domestic TL and LTL for US distribution, and international air freight for high-priority and time-sensitive shipments. The total freight under management exceeded $200M annually across a carrier pool that required continuous market monitoring to manage effectively.
The procurement cycle ran on the team's capacity to process bids rather than on market conditions. Sourcing events required assembling lane data from internal systems, distributing RFQ templates to a diverse carrier pool, normalizing heterogeneous bid formats manually, running cost scenario modeling in Excel, and finalizing awards through an approval workflow that had no automated support. The cycle took long enough that market rates sometimes moved materially between event launch and award finalization — the company was negotiating against data that had aged during the process itself.
Rate management suffered from the same lag. Contracted rates lived in a combination of internal files and carrier-held documents that required manual reconciliation when rates changed or contracts renewed. Bid deviation analysis — identifying when a carrier's submitted bid was anomalous relative to lane history or market benchmarks — happened informally, if at all. The procurement team had market experience but no systematic access to the real-time benchmarking data that would have made that experience more actionable at scale.
The evaluation was driven by a specific time-to-value requirement: the company could not commit to a 3-to-5-month implementation timeline. The procurement cycle needed to improve within weeks, not quarters. Traditional enterprise procurement platforms required heavy configuration, extensive IT involvement, and long deployment timelines that were incompatible with the business's expectations. Freehand's 3–5 week go-live capability was the functional differentiator that moved the evaluation forward.
What Freehand Did
Freehand deployed the AI Procurement platform in 3–5 weeks — covering RFQ creation, bid analysis and negotiation, carrier finalization and awards, and contract and rate management in a single deployment. The AI Procurement Analyst runs sourcing events autonomously from configuration through award recommendation: carrier notification via pre-built bid templates, bid ingestion and normalization regardless of format, intelligent bid deviation analysis that flags anomalies before any human reviews the output, counter-offer suggestion logic based on lane history and market benchmarks, and scenario modeling across cost optimization, incumbent retention, and service-level weighting strategies. The procurement cycle that previously required manual coordination at every step now requires human review only at the decision and approval points.
Rate benchmarking integration connects the AI Procurement Analyst to live market data for all modes in scope — ocean, domestic TL/LTL, and international air — giving the procurement team access to current market intelligence during active bid events rather than relying on historical data and carrier-submitted benchmarks. When a carrier's bid deviates significantly from market rates or lane history, the system flags it automatically with the supporting evidence assembled before the procurement team reviews the bid. The 1–2% freight cost reduction is the validated outcome of moving from manual procurement to AI-driven event management at the $200M+ scale.
The Rate Manager Agent replaced the fragmented rate card management process with a single live repository — all contracted rates across all modes, with versioning, effective-date logic, and accessorial entitlement schedules. When a contract is awarded and rates are finalized, the Rate Manager Agent updates automatically. The gap between what was negotiated and what the audit system knows about contracted rates — a gap that had previously required manual synchronization — is eliminated. Contract renewals trigger proactively based on expiry monitoring rather than being discovered after the renewal window has passed.
The Spend Intelligence Agent provides the global transportation team with real-time freight spend visibility by mode, carrier, lane, and cost center across the full $200M+ network. The procurement decisions the AI Procurement Analyst makes are informed by the same audited spend data the Spend Intelligence Agent tracks — closing the loop between what the company pays and what it negotiates in the next cycle. The team that previously spent most of its time managing a slow procurement process now spends that time on carrier strategy, market analysis, and the decisions that the AI Agents have assembled the data to support.
