Problem

Complex manufacturers often plan around factory-specific machines, materials, labor, priorities, and operating rules, but conventional planning processes leave teams manually firefighting when conditions change. The resulting pain is operational and economic: late orders, planner time spent rescheduling, excess overtime and inventory, unnecessary changeovers, premium freight, and weak visibility into trade-offs.

The core use case is rapid recovery from disruption. When a machine breaks down, a rush order arrives, or materials are delayed, Orvixo is designed to recalculate the knock-on effects and produce a feasible schedule that protects delivery and throughput without forcing planners to rebuild the plan manually.

Product / Service

Orvixo is an AI-enabled advanced planning and scheduling system for complex factories. It builds a live model of the operation by connecting ERP and MRP data with machines, people, capacity, materials, constraints, priorities, and planner knowledge. AI and optimization algorithms then generate end-to-end plans spanning demand, materials, capacity, and production, while planners can review, adjust, and approve each plan.

The system continuously adapts to change, including breakdowns, rush orders, material delays, and shifting priorities, and supports what-if comparisons before a decision is committed. The delivery model is highly hands-on: Orvixo starts with a founder-led review, configures a demonstration around the customer's operation, and, after approval, deploys on site with the factory team with the stated goal of getting the first plan live in about a week. The intended benefits are less firefighting, lower avoidable operating costs, faster recovery, and more reliable on-time delivery.

Market

Orvixo competes in AI-enabled manufacturing planning and optimization, particularly advanced planning and scheduling, production scheduling, and manufacturing operations software for complex industrial companies. Its likely competitive set includes established supply-chain and production-planning platforms such as Kinaxis and o9, alongside APS products including Siemens Opcenter APS, DELMIA Ortems, and Optessa. Orvixo's positioning is more factory-specific and reactive: it emphasizes modeling each operation's unique rules and constraints, continuously replanning as reality changes, and supporting implementation through a founder-led deployment process.

The company appears to be at an early commercial stage. Y Combinator lists Orvixo as a Summer 2026 company founded in 2026, active, and based in London, with a two-person team; the company also says it is backed by Y Combinator. The public materials reviewed do not disclose named customers, revenue, pilot results, or deployment counts, so pre-revenue status cannot be confirmed, but publicly quantified traction is not yet evident.