How A2go Cuts AI Application Delivery in Half with Databricks

A2go is a supply chain AI company that builds agentic AI applications for enterprises with high-volume operational complexity. Its clients include large food producers managing tens of thousands of SKUs across dozens of production facilities, where data from warehouse management systems, ERP platforms, CRM databases, weather patterns, and live market conditions must be synthesized continuously to drive pricing and logistics decisions.

A2go’s prior technology stack created barriers to scale. The team managed disparate tools without a unified data processing layer, lacked Apache Spark for large-scale workload handling, and faced slow iteration cycles that made reacting to changes in customer data a multi-day exercise. Each enterprise engagement required custom infrastructure and large project teams, limiting how quickly A2go could grow.

A2go standardized on the Databricks Data Intelligence Platform, using Unity Catalog for centralized governance and a medallion lakehouse architecture to unlock and transform legacy customer data for AI applications. Lakeflow Jobs handled batch orchestration natively. Databricks Apps provided the deployment layer where agentic AI applications could be built, tested, and iterated without leaving the Databricks workspace. The integrated environment enabled unprecedented component reuse across engagements — A2go restructured delivery into specialized workstreams while dramatically reducing project staffing per customer.

For one of Brazil’s largest beef producers — operating 65 production facilities, 17 sales channels, and more than 150,000 customers — A2go deployed agentic AI applications that continuously analyze regional demand patterns, pricing elasticities, product shelf life, weather conditions, and market fluctuations across more than 60,000 SKUs. Regional demand and pricing forecasts that previously took 28 hours now complete in under one hour. Pricing scenarios across all SKUs can be simulated across multiple markets in minutes. Twenty-five or more users in the market intelligence department now run complex simulations concurrently and independently — replacing a manual process where pricing analysts extracted data into Excel and distributed recommendations that were often stale by the time they reached the sales team.

The deployment positions A2go to replicate this model at scale. Each new engagement leverages components built for previous customers, creating a compounding efficiency effect. The combination of Unity Catalog governance, Databricks Apps deployment, and lakehouse performance has become a reusable foundation that A2go applies across industries — allowing the same lean team to serve more enterprises, faster, with every successive project.