Automated data science for enterprise analytics

BigSquid (acquired by Qlik)

Constant compute cost per customer · Linear infrastructure scaling · Acquired by Qlik

The problem

Enterprise customers needed predictive insights from complex data but lacked data science expertise. Computational costs scaled poorly with dataset size, and the gap between raw data and actionable decisions required specialized skills the customers didn't have.

The approach

Built an automated model training engine with hyperparameter tuning and data quality detection. Designed scalable data pipelines supporting BI tools, databases, and spreadsheets. Optimized storage and compute layers to maintain constant costs per customer regardless of dataset size.

The outcome

Non-technical users could autonomously generate and deploy predictive models. Infrastructure scaled linearly with customer growth while compute costs stayed flat. The platform secured venture funding and validated the market opportunity through Qlik's acquisition.