Inside FourKites Logistics Platform: Data Streaming for AI and End-to-End Visibility in the Supply Chain

Global supply chains face constant disruption. Trade conflicts, wars, inflation, and shifting regulations are making logistics more unpredictable than ever. Traditional systems can’t keep up with the speed and complexity of today’s challenges. This blog post shows how FourKites, a leader in supply chain visibility, uses data streaming with Apache Kafka in the cloud, combined with AI, to power real-time logistics. With over 3 million shipments tracked daily, FourKites delivers more than visibility — it enables fast, autonomous decisions at global scale. Their architecture connects transportation, inventory, and yard operations in one unified platform. This real-time foundation allows customers to respond in seconds, not hours, improving efficiency and resilience across the supply chain.

Join the data streaming community and stay informed about new blog posts by subscribing to my newsletter and follow me on LinkedIn or X (former Twitter) to stay in touch. And make sure to download my free book about data streaming use cases covering various logistics and supply chain use cases and real-world success stories.

At Kafka Summit Bangalore, Arpit Garg and Goutham Elangesh from FourKites shared how they built real-time supply chain visibility. The blog explores their use of data streaming to power FourKites’ logistics platform.

The Logistics Industry: Complex, Global, and Under Pressure

The logistics industry is the backbone of global commerce. Every sector — from manufacturing and retail to healthcare and energy — depends on the seamless movement of goods. Yet today’s global supply chains operate in an environment marked by uncertainty and constant disruption.

Geopolitical tensions are reshaping trade routes and regulations. The ongoing U.S.–China tariff conflicts have increased the complexity of sourcing and distribution strategies. The war in Ukraine, and broader instability in Eastern Europe, has constrained key transport corridors and created energy-related ripple effects across supply chains. In the Middle East, escalating tensions between Israel and Iran continue to disrupt airspace and shipping lanes, adding risk and cost for global carriers.

These disruptions are no longer rare exceptions. They are part of the operating landscape. Combined with rising protectionism, inflationary pressures, and a volatile global economy, logistics networks must now adapt faster than ever. Traditional batch-driven systems are not built for this level of volatility.

Most logistics companies — from asset-light digital freight brokers to large third-party logistics providers (3PLs) — still face a common challenge: a lack of real-time visibility across shipments, inventory, facilities, and orders. Disconnected systems and delayed data create blind spots. Businesses struggle with late deliveries, missed service-level agreements, manual exception handling, and inefficient asset utilization.

To remain competitive, logistics leaders must move from fragmented, reactive workflows to real-time, connected operations. Accurate and consistent data, processed and shared within seconds — not hours or days — is no longer optional. It is the foundation for operational resilience, cost control, and strategic agility in an increasingly unstable world.

FourKites: The Platform Powering Supply Chain Visibility and Autonomous Logistics

FourKites is a global leader in real-time supply chain visibility, trusted by more than 1,600 of the world’s largest brands. Its platform provides deep transparency across every major supply chain function — including transportation, inventory, order management, and yard operations.

With over 3 million shipments tracked daily, FourKites operates the largest and most comprehensive supply chain data network in the world. Given the company’s rapid growth and expanding customer base, the figures shared in 2024 at the data streaming conference Current in Bangalore have likely already been surpassed.

FourKites has been consistently recognized as a Leader in the Gartner Magic Quadrant for Real-Time Transportation Visibility Platforms (RTTVP), reflecting its strong execution, innovation, and broad customer adoption.

Intelligent Control Tower Unifying Real-Time Data, Digital Twins and AI

At the core of its offering is the Intelligent Control Tower™, a powerful suite that unifies real-time data, digital twins, and AI to give businesses predictive, actionable insights across their global operations. The system goes beyond visualization — it enables real-time exception handling, automated execution, and predictive scenario planning.

Key platform capabilities include:

• Real-Time Transportation Visibility: Track shipments across all modes — truckload, ocean, rail, air — in real time, with predictive ETAs and alerts for delays or disruptions.
• Digital Twins of the Supply Chain: Continuously updated digital representations of orders, shipments, inventory, and facilities provide a living model of current operations.
• AI-Powered Digital Workers: Intelligent agents automate routine tasks like carrier updates, appointment scheduling, and delay notifications — reducing manual effort by up to 80%.
• Connected Inventory and Order Management: Gain real-time views of stock levels and order flows to make faster decisions around replenishment and fulfillment.
• Yard and Facility Optimization: Enhance throughput and reduce dwell times through automated scheduling, check-in/check-out, and gate operations using tools like AutoGate AI and Yard Connect AI.
• Inbound and Outbound Logistics Optimization: Solutions like PO Connect AI and Customer Connect AIstreamline vendor collaboration, inbound scheduling, and last-mile performance.
• MyWorkspace: A customizable command center for operators and executives, providing tailored dashboards, cross-product analytics, and unified insights to support connected decision-making.

Together, these capabilities form a system built for autonomous supply chain action — enabling organizations to move from reactive firefighting to proactive and predictive logistics.

FourKites’ focus is not just visibility — it’s intelligent orchestration. By combining real-time data streaming with advanced analytics and machine learning, the platform empowers customers to increase agility, reduce operational costs, and improve service levels across their end-to-end supply chain.

From Siloed Data to a Real-Time Supply Chain Control Tower with Data Streaming

Legacy logistics systems rely heavily on batch data pipelines. This creates siloed views of operations and limits responsiveness. To overcome these challenges, companies like FourKites are adopting modern data streaming architectures. Apache Kafka and Apache Flink form the backbone of this transformation.

For a detailed overview of how streaming enables a real-time Control Tower, refer to this blog post on Supply Chain Control Towers with Apache Kafka.

Apache Kafka acts as the central nervous system for data movement, capturing events as they happen — shipments delayed, trucks entering yards, orders picked. Apache Flink enables real-time processing, transformation, and enrichment of this data. The result is continuous intelligence that powers faster, better business decisions.

FourKites’ Intelligent and Autonomous Control Tower Powered by Data Streaming and AI

FourKites has rearchitected its systems to build a truly intelligent control tower. Arpit Garg (Senior Principal Architect) and Goutham Elangeswaran (Staff Data Engineer) shared the technical journey at Kafka Summit Bangalore. Their team used Confluent Cloud to support scalable, low-latency data pipelines.

Key highlights include:

• Streaming Data Ingestion: Kafka powers ingestion pipelines that can transform and route data in less than one second.
• Scalable Write Capacity: Systems scale to handle 8,000+ writes per minute, supporting millions of daily events.
• Real-Time Joins Across Domains: Orders, shipments, yard updates, and inventory data are joined in milliseconds for unified insights.
• Multi-Tenant Design: The architecture supports multiple product lines with high availability and customization.
• Cloud-Native Efficiency: Leveraging Confluent’s fully managed services reduced both operational overhead and compute costs.

The result is a control tower that’s not just reactive but predictive and autonomous. Digital twins leverage data streaming to provide live models of assets, orders, and facilities. AI agents automate decisions like rescheduling pickups or alerting teams to potential risks. Manual processes are reduced by 80%, and throughput increases without adding headcount.

FourKites MyWorkspace: Custom Intelligence for Supply Chain Leaders

FourKites MyWorkspace is a configurable analytics interface for supply chain stakeholders. Built on Kafka and real-time data architecture, it enables:

• Tailored dashboards for different user roles
• Real-time and historical metrics in a single view
• Fast development of new widgets and modules
• Unified cross-product analytics and recommendations

MyWorkspace highlights the shift from fragmented applications to a connected data platform. It empowers users to surface actionable insights — like accelerating unloading of a trailer carrying low-stock SKUs — at the moment they’re needed.

From Lambda to Kappa Architecture: Data Streaming as Event-Driven Backbone

The shift to a Kappa architecture — where both real-time and historical data are handled through a single stream — was a strategic move by Fourkites. Instead of building separate ingestion paths for batch and streaming, FourKites unified its data platform on Kafka.

The above diagram shows FourKites’ transition from Lambda to Kappa architecture (without explicitly naming it). Key elements include:

• Metadata-Driven Ingestion: App teams simply publish to Kafka; ingestion pipelines handle formatting and routing based on metadata.
• Centralized Reporting Framework: Built in-house to deliver customizable dashboards and real-time widgets.
• Cross-Product Data Consistency: All systems share a consistent view of data, filters, and latency requirements.

The improvements were tangible. Time-to-market for new features was reduced by 50%. Teams onboarded more quickly, and the platform supported complex analytical use cases with better performance and reliability.

Read more about the evolution of the Kappa architecture in the past years: The Rise of Kappa Architecture in the Era of Agentic AI and Data Streaming.

Measured Outcomes from Real-Time Architecture: Operational Gains and Strategic Benefits

The technical investments led to clear business value:

• Faster customer onboarding and product launches
• Stronger cross-product insights for strategic decision-making
• Reduced manual work and improved operational efficiency
• Ability to surface actionable alerts in minutes, not hours or days

With its Intelligent Control Tower, FourKites has moved beyond visibility into the realm of autonomous execution. The platform not only identifies risks but also triggers the next best actions automatically.

The Future of Logistics and Supply Chain with Data Streaming using Apache Kafka and Flink

The logistics industry is undergoing rapid digital transformation. Global trade, e-commerce, and rising customer expectations are key drivers. At the same time, geopolitical tensions add new pressure. U.S.–China tariffs and conflicts in Ukraine and the Middle East disrupt supply routes and increase risk. Supply chains must now react in real time to stay resilient and competitive.

Data streaming offers logistics and supply chain leaders the foundation for:

• Predictive disruption management
• Proactive inventory and order planning
• Smarter resource allocation and scheduling
• End-to-end collaboration with partners and customers

As shown by FourKites, modern supply chains require more than data — they need continuous intelligence. Apache Kafka and Flink are at the heart of this shift. Real-time architectures not only deliver better business outcomes but also enable the flexibility and scale needed for future growth.

This success story illustrates a clear path to higher ROI and innovation speed. By investing in cloud-native streaming platforms, organizations reduce integration friction, speed up insights, and unlock automation at scale. Data streaming is no longer an emerging trend — it is the new enterprise backbone.

Learn more about data streaming for supply chain and logistics use cases:

• Overview about Real-Time Logistics, Shipping, and Transportation with Apache Kafka at USPS, Swiss Post, Austrian Post, DHL, and Hermes
• Real-Time Innovation in Manufacturing and Logistics with Data Streaming at Siemens
• How Penske Logistics Transforms Fleet Intelligence with Data Streaming and AI

For logistics providers seeking to modernize, the path is clear. It starts with streaming data—and the possibilities grow from there. Join the data streaming community and stay informed about new blog posts by subscribing to my newsletter and follow me on LinkedIn or X (former Twitter) to stay in touch. And make sure to download my free book about data streaming use cases.