Order intelligence platform for ERP-integrated profit optimization
Cavallo sells profit maximization software to product-centric distributors and manufacturers running Microsoft Dynamics or Business Central. The stack reveals a company deeply embedded in the ERP ecosystem (Dynamics GP, Business Central, Power Automate, OData) while building AI-driven analytics on top (Python, scikit-learn, LightGBM, XGBoost). Active projects around predictive models, natural-language interfaces, and cloud transformation suggest they're evolving from legacy rule-based order processing into an AI-assisted decision layer—a shift validated by their hiring focus: product roles are being scaled (3 of 6 open) while sales and support remain lean.
Cavallo builds order intelligence software that integrates with enterprise ERP systems to reduce order errors and margin leaks. Founded in 2003 and headquartered in Grand Rapids, Michigan, the company serves 51–200 employees and focuses on mid-market distributors and manufacturers who rely on Microsoft Dynamics platforms. Their product suite addresses the operational complexity of B2B workflows through data-driven insights and process automation, with recent development efforts centered on cloud migration, predictive modeling, and expanding design capabilities for the distribution segment.
Cavallo integrates with Microsoft Dynamics GP, Microsoft Dynamics 365 Business Central, and other leading ERPs. They are a Microsoft and Intuit certified partner and ship native connectors via Power Automate and OData.
Core stack: C#, SQL Server, Power Automate for automation. Analytics: Python, Pandas, scikit-learn, LightGBM, XGBoost for predictive models. Design and collaboration: Figma, Jira, Confluence. Marketplace: Shopify, Avalara tax, SPS Commerce.
CAVALLO's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.