Pallet Introduces Signals, Bringing Real-Time External Events Into Enterprise AI Decisions
Powering the physical economy with continuous intelligence and reasoning
SAN FRANCISCO, October 20, 2026--Pallet, the company building AI systems that move the physical economy, today announced Signals, a new capability that brings live external events into agent decision-making by connecting what is happening in the world with an enterprise's operational data and institutional knowledge.
Supply chains run on conditions that change by the hour. Tariffs shift, materials fall short, ports slow down, and weather disrupts routes. Yet the systems that track these changes rarely connect with the systems running day-to-day operations, leaving companies to determine manually what a disruption means for their business and how to respond.
"The physical economy runs on an enormous amount of knowledge and expertise, much of it still trapped in legacy systems and in people's heads," said Sushanth Raman, Founder and CEO of Pallet. "AI has the potential to unlock that capacity and fundamentally change how the world produces and moves the food, products, and materials we rely on every day. Signals is another step toward making that possible."
From signal to action
For a global automaker, an aluminum shortage could affect production schedules, customer orders, inventory, transportation, warehouse capacity, and service commitments. Understanding that impact requires connecting information fragmented across ERP systems, transportation platforms, legacy infrastructure, emails, portals, and the institutional knowledge of the people running the operation.
Signals bring that context together. It connects an external disruption to the parts of the business it could affect, traces dependencies across the operation, and helps determine how the company should respond as conditions change.
Signals provides four core capabilities:
External and enterprise context. Connects real-world events, including tariffs, material shortages, weather, and disruptions, with the data and knowledge to understand what they mean for a specific business.
Native access across enterprise systems. Works across the systems where operations run, from modern APIs to ERPs, TMSs, WMSs, AS/400, remote desktops, email, and web portals, allowing agents to reason across fragmented representations of customers, orders, inventory, shipments, and capacity.
Reasoning across dependencies. Updates reasoning and response as new information arrives and conditions change. Traces how a change in one area can affect customers, orders, inventory, transportation, facilities, and capacity across the operation.
Enterprise-owned intelligence. Keeps operational context, persistent memory, and the AI stack under the enterprise's control, with governance over what agents can access, decide, and execute.