Xometry, Inc. introduces its new Enterprise Machining Lead Time Prediction Model and enhanced dynamic pricing logic. These releases expand the Xometry Instant Quoting Engine®, strengthening Xometry’s proprietary data advantage and deepening the design-to-fulfillment intelligence that powers its AI-native marketplace.
Together, these advancements deliver higher prediction accuracy, improved operational efficiency, and expanded rapid lead-time options.
New enterprise machining lead time prediction model
As AI reshapes expectations in manufacturing, Xometry continues to advance its proprietary Instant Quoting Engine, which leverages deep learning trained on real-world production and delivery data from its extensive global Partner Network of manufacturing suppliers. This continuously expanding dataset enables Xometry to dynamically refine market-driven lead time options while improving reliability and execution speed for enterprise buyers.
The new Enterprise Machining Lead Time Model represents a significant expansion of Xometry’s predictive intelligence capabilities, enabled by the scale and depth of performance data generated across its global Partner Network.
Key impacts of this release include:
- Superior prediction accuracy: The model provides customers with more reliable timelines for their custom-ordered parts, having achieved a significant improvement in RMSLE (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: Beyond enabling faster turnarounds, the model will drive a reduction in standard lead time offering for Xometry’s customers.
- Expanded feature integration: The updated model leverages a training dataset four times larger than previous versions and now factors in critical overhead requirements, including specialized certifications (example AS9100D, ISO 9001), new materials, and advanced finishing options (example PTFE Impregnated Hard Anodize, Black Oxide).
Personalized pricing for optimized sourcing
Complementing these speed advancements, Xometry is enhancing the dynamic pricing logic that powers the pricing intelligence layer of its Instant Quoting Engine.
In contrast to traditional supply chain software, which relies on static pricing rules or predefined cost tables, Xometry utilizes a “conversion rate model” that analyzes unique geometric features, quote configurations, and customer-specific historical data to construct a price-response function for every individual quote and part.
Following successful user testing in Q4 2025, these models are being deployed more broadly to U.S. customers in Q1 2026, with the goal of improving the buyer and partner experience and increasing revenue per user.
Accelerating the Marketplace Flywheel
“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,” said Vaidy Raghavan, Chief Product & Technology Officer at Xometry.
Xometry’s proprietary 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. Each completed order strengthens future predictions, increasing accuracy, speed, and reliability across the network.
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