Xometry Enhances AI-Native Marketplace with Enterprise Lead Time Intelligence

Xometry, Inc. has released its new Enterprise Machining Lead Time Prediction Model and enhanced dynamic pricing logic. These releases expand the Xometry Instant Quoting Engine.

Enterprise Machining Lead Time Prediction Model

The new Enterprise Machining Lead Time Model represents an expansion of Xometry’s predictive intelligence capabilities, enabled by the scale and depth of performance data generated across its global Partner Network.

Key impacts include:

• Prediction accuracy: The model provides timelines for their custom-ordered parts, having achieved improvement in Root Mean Squared Logarithmic Error compared to its predecessor.
• Expanded rapid delivery offerings: Based on learning from Xometry’s historical supplier performance dataset, the model now optimizes for and facilitates 1-day lead times across a growing catalog of materials and geometries.
• Enhanced operational throughput: The model will drive a reduction in standard lead time.
• Expanded feature integration: The updated model leverages a training dataset four times larger than previous versions and now factors in overhead requirements, including specialized certifications (example AS9100D, ISO 9001), new materials, and advanced finishing options.

Personalized Pricing for Optimized Sourcing
Xometry is enhancing the dynamic pricing logic that powers the pricing intelligence layer of its Instant Quoting Engine. Xometry utilizes a "conversion rate model" that analyzes geometric features, quote configurations, and customer-specific historical data to construct a price-response function for every individual quote and part.

After successful user testing in Q4 2025, these models are being deployed more broadly to U.S. customers in Q1 2026, to improve the buyer and partner experience and increasing revenue per user.

"This release represents more than just an incremental update; it is a foundation for future innovations and a fundamental shift in how we approach manufacturing speed and reliability at scale," says Vaidy Raghavan, chief product and technology officer at Xometry. "By closing the data loop with our Partner Network and accelerating model deployment cycles through continuous training, we have reduced the time from insight to production impact. This allows us to solve complex, context-dependent sourcing challenges that static software or isolated AI agents cannot address."

Xometry’s pricing and sourcing models are embedded directly within live marketplace transactions, integrating digital quoting, supplier selection, production performance, and delivery outcomes into a closed-loop learning system. 

By embedding design-to-fulfillment intelligence directly into engineers’ workflows, Xometry reduces information asymmetry in manufacturing procurement.

Sources: Press materials received from the company and additional information gleaned from the company’s website.