Project44 is adding the AI Freight Procurement Agent to its Intelligent TMS platform and automating carrier selection, rate comparison, and negotiations across modes. The new agent is replacing static, periodic bid cycles and spreadsheet-based negotiations with continuous, AI-based sourcing, mini-bids, and renewal negotiations within defined guardrails. From a supply chain perspective, project44, founded in 2014 by Jett McCandless in Chicago, competes against FourKites, Shippeo, Tive, Overhaul, and Wakeo in the real-time visibility platform space. The company introduced its Intelligent TMS product under the Movement brand in 2024, thereby expanding from visibility into the execution domain. Insight Partners, TPG, Goldman Sachs, Emergence Capital, and Sapphire Ventures are leading investors in project44.
Jett McCandless, founder and CEO of project44, stated: "Freight procurement is one of the largest controllable cost drivers in the supply chain. Intelligent TMS lays the foundation for continuous optimization. The AI Freight Procurement Agent transforms analytics into autonomous action within defined guardrails, delivering measurable savings while maintaining full control." From a supply chain perspective, the traditional flow of freight procurement consists of stages including RFP (Request for Proposal), RFQ (Request for Quotation), RFI (Request for Information), annual bid, mini-bid, spot market, routing guide, tendering, award allocation, and contract execution. Platforms such as Sleek Technologies, Emerge, Loadsmart, Convoy (shut down), Uber Freight, C.H. Robinson, and Transfix offer similar automation capabilities in the digital freight matching space.
From a supply chain perspective, agentic AI is a next-generation AI architecture that not only analyzes data but gains the ability to take action without human intervention. Agents developed by OpenAI, Anthropic, Google DeepMind, Microsoft, Salesforce (Agentforce), SAP (Joule), Oracle, and ServiceNow are being integrated into supply chain software. The concept of guardrails is based on NIST AI RMF, EU AI Act, and ISO/IEC 42001 standards and limits the permitted action space for AI agents. Multi-agent system architectures are built with orchestrator, specialist agent, verifier agent, and human-in-the-loop components. Reinforcement learning from human feedback (RLHF), chain-of-thought reasoning, tool use, and retrieval-augmented generation (RAG) are core technical components of modern agentic AI.
From a supply chain perspective, the Intelligent TMS category combines real-time visibility, execution, procurement, and analytics on a single platform, unlike traditional TMS (SAP TM, Oracle OTM, Manhattan TMS, BluJay, MercuryGate, Descartes, Trimble TMS, 3Gtms) providers. The shortcomings of the annual bid cycle become evident in market volatility — particularly during diesel price fluctuations, capacity crunch, port congestion, and peak season periods. Strategies such as continuous procurement, dynamic pricing, spot/contract blend, capacity reservation, and strategic carrier partnership are becoming new-era shields for shippers. Lane analytics, carrier scorecard, OTIF (On Time In Full), tender acceptance rate, and cost per mile metrics are data inputs for AI-driven decision mechanisms. Ultimately, project44's AI Freight Procurement Agent represents a tangible example of the transition from visibility to autonomous execution.
Key Points:
1. Project44 is adding the AI Freight Procurement Agent to Intelligent TMS.
2. Static bid cycles and spreadsheet negotiations are transforming into continuous AI sourcing.
3. Mini-bids and renewal negotiations are automated within guardrails.
4. Jett McCandless identifies freight procurement as the largest controllable cost driver.
5. Autonomous action is balanced with maintained control.
