Ever.Ag unifies 19 data systems with an AWS-based lakehouse
Multiple acquisitions left Ever.Ag with fragmented systems that limited visibility and slowed effective analysis.
About
Ever.Ag is a global AgTech provider supporting dairy, crops, animal protein, and agribusiness supply chains with software, services, and market intelligence. Their tools help customers operate with clarity across operations, finance, and risk. Over decades of growth, the organization has expanded its reach across every layer of agricultural production.
As the company grew, each line of business developed its own systems, data structures, and reporting models. This created gaps in visibility across subsidiaries and made it difficult to align on shared metrics. Executives needed a clearer view of performance across product lines, markets, and operational units.
Ever.Ag partnered with Lumenalta to lay the groundwork for a unified data foundation. The goal was to create a consolidated architecture capable of supporting firmwide reporting, scalable analytics, and new business opportunities.
Firmwide
data dictionary and governance structure created
19
disconnected data systems into one modern architecture
$2M
investment in AWS-based data lakehouse unlocked an additional half-turn in EBITDA
Challenge
Ever.Ag’s acquisition strategy resulted in 19 subsidiaries operating with separate databases, custom workflows, and application-specific models. The organization lacked a shared data environment, making it difficult to produce cross-functional reporting or gain a full picture of operational health.
Business leaders were often limited to local insights from individual systems rather than a consistent company-wide view. This created delays in analysis, inconsistencies in metrics, and friction when evaluating new opportunities. A unified architecture was required to bring scattered information into a single, scalable structure.
Key challenges included:
- Disconnected data systems across 19 acquired companies
- Inconsistent data pathways and access methods across custom and third‑party tools
- Limited ability to perform holistic reporting across subsidiaries
- Multiple application models requiring a full inventory and mapping effort
- Fragmentation that restricted visibility into emerging insights and product opportunities
- Difficulty maintaining governance across siloed systems
- A need for a scalable architecture capable of supporting growth
A consolidated data lakehouse was identified as the path to create a single source of truth, strengthen governance, and position Ever.Ag for analytics‑driven growth.
Solution
Lumenalta began with a full data inventory assessment across all 19 acquired companies. The team evaluated databases, APIs, data structures, and third‑party tools to build a clear map of existing assets and integration points. This created the foundation for a unified approach to modeling, governance, and architecture.
We delivered a proposed company-wide data dictionary, a common data architecture, and an extensible design for a modern data lakehouse on AWS. The blueprint included functional components, technology recommendations, and an implementation roadmap.
The technical specification outlined the use of AWS Lake Formation, DMS, Glue Catalog, Managed Airflow, and Apache Iceberg on S3, supported by a zero‑copy ETL API framework. These components together form a scalable platform designed for analytics, governance, and firmwide reporting.
This work establishes a stable foundation for centralized insights, operational alignment, and future data‑driven product development.
Results
The project provided Ever.Ag with the clarity and structure needed to build a modern data platform capable of supporting strategic growth. With a unified architecture and roadmap, the organization is positioned for more consistent reporting, richer insights, and improved visibility.
Key outcomes include:
- Firmwide data architecture and governance framework created
- Clear data dictionary and catalog structure established for long‑term alignment
- Unified view across 19 systems through a consolidated data model
- Scalable AWS-based lakehouse design prepared for implementation
- Stronger reporting foundation for enterprise‑wide decisions
- New insights and product opportunities supported by centralized data management
- A platform positioned to help unlock new revenue opportunities
A unified data foundation now supports clearer analysis across the organization, creating the structure needed for operational alignment and informed planning.
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