The FourKites Knowledge Center

AI explainability in supply chain is the ability to provide human-understandable explanations for every AI-generated prediction, recommendation, or action, answering not just 'what did the AI do' but 'why did it do that' and 'what information informed the decision.'

AI Decision Intelligence is the accumulated library of supply chain decision precedents: what resolution paths worked, for which exception types, on which carrier-lane combinations, in which seasons, captured from millions of real agent actions.

Sophie is FourKites' AI Developer Agent that translates natural-language descriptions of supply chain processes into production-ready Agent Operating Procedures (AOPs), connected to the Graph and Digital Twins, deployable in days.

An Outcome Advisor is a FourKites specialist who helps enterprise buyers identify which supply chain outcomes apply to their operation and designs the deployment path to deliver them.

Systems of Agents is the architectural pattern in which multiple AI agents coordinate to resolve complex situations that span functional boundaries, where one agent's output triggers another agent's action, enabling end-to-end autonomous resolution without human coordination between steps.

See-Reason-Act-Learn is the four-stage operational cycle that defines a true Intelligent Control Tower: seeing disruptions across the entire supply chain, reasoning about downstream consequences, acting through autonomous AI agents, and learning from every decision to improve future responses.

Gen UI (Generative UI) is a capability within FourSight AI that dynamically generates custom, persona-specific supply chain interfaces without manual configuration or dashboard building.

EDI 214 (Transportation Carrier Shipment Status Message) and EDI 990 (Response to a Load Tender) are standard electronic data interchange formats used for carrier-shipper communication. EDI 214 transmits shipment status updates (picked up, in transit, delivered). EDI 990 transmits carrier acceptance or rejection of a load tender.

Generic AI agent platforms (LangChain, CrewAI, AutoGen, and consulting-led custom builds) consistently fail in production supply chain environments because they lack network intelligence, cross-boundary orchestration, and decision memory.

When deploying AI agents in supply chain, 80% of every workflow should leverage proven patterns from the network (pre-built AOPs validated across Fortune 500 deployments) and 20% should be customized to the customer's specific business rules, escalation paths, and integration requirements. This framework explains why this ratio matters and how to apply it.

The distinction between supply chain AI powered by a multi-enterprise network (cross-company intelligence from hundreds of shippers) versus AI powered by a single customer's data (limited to one company's operational history).

Cross-Company Intelligence is the layer of supply chain insight that emerges only when operational data from multiple enterprises is aggregated: carrier behavior patterns, facility benchmarks, lane performance distributions, and exception resolution precedents that no single company could observe alone.

FourSight AI is the intelligence and analytics layer of the FourKites platform, providing conversational analytics, generative interfaces (Gen UI), automated scorecards, and the bridge from insight to autonomous action.

An Intelligent Control Tower is a supply chain platform that sees, reasons, acts, and learns, completing the full cycle from disruption detection to autonomous resolution without requiring a human in the operational path.

Loft is FourKites' multi-agent orchestration platform where AI agents operate, workflows are built, and every decision is recorded with a full audit trail.