What We Did

Designed and implemented a scalable data lake and analytics infrastructure to unify research operations.
Developed an ontology and data model to semantically integrate microbial engineering and plant science.
Advised on integration of lab information systems, workflow management tools, and machine learning platforms.
Created an implementation roadmap to guide incremental system adoption and long-term scalability.

The Challenge

A biotech startup focused on agricultural innovation needed to unify its microbial engineering and plant science operations into a single data framework. As a rapidly growing organization, it required scalable infrastructure to support lab systems, field data, and advanced analytics while maintaining the flexibility to adapt to evolving scientific needs.

Lifescale Analytics’ Solution

Lifescale Analytics designed a data lake architecture that integrated multiple systems into a unified analytics environment. The team built an ontology and semantic data model to standardize data across research areas, ensuring interoperability and consistency. By documenting an implementation roadmap, we enabled the startup to adopt systems incrementally while keeping operations streamlined during its growth phase.