The FourKites Knowledge Center

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.

Outcome as a Service is a commercial model in which an enterprise pays for measurable business outcomes delivered by AI agents, rather than software licenses, seats, or modules.

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).

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

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.

A Supply Chain Digital Workforce is a team of named AI agents that autonomously perform supply chain operations (exception resolution, document processing, appointment scheduling, customer communication) using cross-company intelligence from a network graph.

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.

Conversational analytics in supply chain is the ability to query supply chain data using natural language (typed or spoken) and receive instant, data-grounded answers with visualizations, eliminating the need for pre-built dashboards, analyst support, or SQL expertise.

The Supply Chain AI Flywheel is the compounding intelligence cycle in which more data feeds better intelligence, better intelligence feeds smarter agent decisions, agent decisions generate decision traces that enrich the data, and the system gets stronger with every shipment processed.

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.

A supply chain Digital Twin is a live, connected digital replica of supply chain objects (orders, shipments, facilities, inventory, assets) that continuously updates from execution systems and traces the impact of disruptions across every connected entity in real time.

Agent Communication Channels are the modalities through which supply chain AI agents reach carriers, suppliers, customers, and enterprise systems: Email, SMS, System-to-System API, Portal/UI, EDI, and Voice.

Decision Intelligence is the discipline of using data, analytics, and AI to improve the speed and quality of operational decisions, encompassing the capture of decision context, the evaluation of alternatives, the execution of the chosen action, and the measurement of outcomes to inform future decisions.

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.