FourKites, the leader in AI-powered supply chain transformation, today announced Outcome-as-a-Service for Supply Chain™. The go-to-market model centers on the business results that customers answer for. In addition, a new company mission puts a number on the model. FourKites pledges to use AI agents to complete one billion hours of operational work over the next decade.
The shift reflects the company’s assessment of how enterprise software is changing. As AI matures, customers care less about the tools themselves. Instead, they value the completed work those tools were meant to produce. A typical Fortune 2000 supply chain runs on 10 to 15 separate tools. Each tool optimizes one function. However, few companies can connect them to the cost, service and revenue mandates their executives set.
Outcome-as-a-Service for Supply Chain starts with those mandates. Each engagement begins with the number a customer is on the hook for. Examples include on-time-in-full performance, expedited freight spend or cost to serve. FourKites then works backward to the AI agents, workflows and data needed to move that number.
“We founded real-time visibility to show customers where the problem was. Outcome-as-a-Service is how we solve it for them,” said Mathew Elenjickal, founder and CEO of FourKites. “Every leader we work with is accountable for an outcome, not a capability. A VP of supply chain isn’t measured on whether they’ve adopted AI. They’re measured on whether product arrives on time and in full, at the right cost.”
The Network Behind Every Outcome
Committing to outcomes means FourKites AI agents resolve problems on a customer’s behalf. They no longer just flag them. Notably, that kind of autonomous execution is only as reliable as the context behind each decision. Most enterprise AI runs on a company’s internal data. That data describes what happens inside its own four walls. However, the signals that decide whether an outcome is met sit outside any single company’s systems. These include carrier performance on a lane and conditions at a port or a receiving dock.
The FourKites network graph connects 1,600+ brands, 500,000+ carriers and 3.6 million facilities across 176 countries. FourKites AI agents draw on that context before every action. They also learn from what happens after it. As a result, each prediction and decision is more accurate than a model trained on one company’s data alone. Over time, the agents improve their performance for each customer.
“AI models are becoming a commodity. What can’t be copied is real-world network data and the context around it,” Elenjickal said. “That context is what lets our agents act on a customer’s behalf, and it’s why we can commit to outcomes.”
For more than a decade, FourKites’ mission centered on building that network. The new mission, in contrast, measures the work the company completes for customers. To deliver outcomes at that scale, FourKites rebuilt every internal function to operate AI-natively over the past year. Engineering, for example, automated the software development lifecycle end to end. The team moved from biweekly releases to continuous daily releases.
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News Source: Businesswire.com
