We help middle market companies act on data
Data and Software Engineering Lab focused on building next generation applications to automate core business processes
Who we are
We are a team of 10+ data and software engineers with backgrounds from AWS, Apple, Doordash, Lazard and Stanford.
How we work
Discovery and Data Strategy
Through interviews and workshops, we’ll build a solid understanding of your business, industry, strategic objectives and challenges. We then collaboratively identify opportunities and focus areas with clear ROI to draw up your data roadmap and strategy.
Architecture and Modeling
We sit down with your technical team to go through technology selection, technical specs & other requirements. We then draw up our vision for your application and its data infrastructure, optimizing for performance, security and reliability. .
Iterative Implementation
Our development process is phased and designed to be highly engaging. We operate on a sprint cadence. Frequent touch points with business and technical stakeholders allow us to incorporate your thoughts, preferences, and suggestions.
Selected Projects
Paperless claims management system for an insurance provider that reduced claim resolution time from 21 days to 3 days. Solution included workflow management, fraud detection, and payment processing integration.
End-to-end, AI-powered platform for a telehealth client that enabled a 2.5x increase in patient conversation throughput (auto-complete and discharge document generation features).
Customer 360 portal for a supermarket chain’s support agents to have a comprehensive view of account information and history when resolving inquiries. This led to a 38% increase in customer satisfaction.
Self-Service business intelligence implementation for an entertainment streaming provider. Built a logical data layer to measure cohort performance, customer lifetime value and churn. This enabled a data-driven promotional strategy.
Marketing Performance measurement dashboards for an e-commerce provider. Built a comprehensive attribution data pipeline to quantify effectiveness and forecast ROAS on a per-channel basis. This allowed the client to re-allocate budget spend to the highest performing channels.
Cloud data warehouse design and implementation for a client in the trucking industry. Pulled, unified and modeled data from various sources (ERP, CRM, Social, Application databases) for efficient and accurate retrieval.
