Infios Launches AI Agents for Supply Chain Execution Workflows

Supply chain software vendor Infios announced a new suite of AI agents designed to operate inside execution workflows rather than as separate analytical tools. The April 30, 2026 release marks a shift from passive monitoring to active orchestration across order management, warehouse operations, and transportation.

The announcement comes via official Business Wire press release, which details four distinct agent categories. Transportation Agents handle driver check calls through AI-powered voice interfaces triggered by specific conditions. Order and Document Agents process unstructured files like bills of lading, converting them into structured data without manual entry. Warehouse Agents assist supervisors with inventory research and labor coaching. Optimization Agents evaluate routing and fulfillment options in real time, automatically reassigning loads when disruptions occur.

This isn't another dashboard that tells you what's wrong. The agents actually fix things.

Infios CEO Ed Auriemma framed the launch around a core problem: disruption has become the baseline, not an exception. Legacy systems react after damage is done. The new architecture embeds intelligence directly into execution, creating what the company calls a continuous sense-decide-act-learn loop. The goal is moving from manual intervention to automated action, executing without interruption.

Customer metrics cited in the announcement show measurable outcomes. A global apparel firm reduced order release times from hours to minutes. A US online retailer cut backorders by 70 percent in production environments. A leading logistics service provider achieved an 83 percent autonomy rate for automated order entry. Disruption detection and recovery now happens in minutes instead of days across all customers.

These numbers sound impressive on paper (and they probably are, but supply chain folks know implementation is where the rubber meets the road). The real question is whether organizations can actually deploy this at scale without breaking existing workflows.

Autonomy is deployed gradually, not all at once. Infios AI operates within customer-defined guardrails and advances through three stages. Stage 1 is Assisted, where agents recommend actions with clear rationale. Stage 2 is Automated, with AI executing within defined policies. Stage 3 is Autonomous, where operational decisions execute end-to-end within guardrails. Teams can start with a single high-impact workflow like delayed shipments or order changes, then expand as the system proves itself.

The technology builds on a November 2025 collaboration between Infios and Amazon Web Services. That partnership integrated generative AI agents into Infios Order Management using AWS Bedrock and Strands Agents. The collaboration was set to launch in early 2026, aligning with this broader agent rollout. Eugene Amigud, Chief Innovation Officer at Infios, noted the agents proactively detect and resolve anomalies during fulfillment, rebalance orders across networks, and predict delivery times before issues arise.

From a technical standpoint, the architecture matters. These agents run inside Infios's execution systems, not to replace them but to orchestrate them. A decision in one domain triggers coordinated action across all others. When a carrier delay hits, picking falls behind, and order promises are at risk, Optimization Agents evaluate inventory, capacity, and routing across systems, then automatically reassign, reprioritize, and re-tender in minutes without manual intervention.

Infios is a joint venture of international technology provider Körber and global investment firm KKR. The company serves more than 5,000 customers across 70 countries, positioning this as a modular, adaptable execution system where each component works independently with decisions and actions coordinated in real time.

Physical interaction with the system changes. Transportation Agents use voice interfaces for driver check calls, which means warehouse managers aren't staring at screens waiting for status updates. Order and Document Agents eliminate manual data entry from unstructured files, reducing the friction of clicking through portals or waiting for EDI transmissions. The sensory experience shifts from reactive monitoring to proactive orchestration.

Whether organizations actually trust AI to execute operational decisions without human oversight remains the real question. The graduated autonomy model addresses this, but supply chain leaders have seen plenty of automation promises that required more human intervention than expected. The customer metrics are compelling, but implementation complexity and integration with existing systems will determine whether this delivers on the "execution without interruption" claim.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn