Lume

Lume was a software platform designed to solve the problem of customer data integration for software teams. Its core function was to eliminate the long, manual process of connecting a new customer’s existing data systems—such as legacy ERPs, custom databases, and schemas with inconsistent structures—into a team’s own infrastructure. Traditionally, onboarding a single customer could take days or even weeks of engineering effort, requiring engineers to reverse‑engineer schemas, write custom transformation scripts, and handle data quality issues manually. Lume automated these steps using artificial intelligence. The platform first performed schema discovery: it automatically scanned incoming data sources, identified table structures, field types, relationships, and anomalies. Then it suggested intelligent data mappings between the customer’s data schema and the team’s target schema, reducing the need for tedious manual matching. After the mapping was defined, Lume validated data quality by checking for missing values, type mismatches, duplicate records, and other common issues, flagging problems before they entered production. Finally, Lume generated dbt (data build tool) code automatically, producing ready‑to‑run transformation pipelines that engineers could deploy directly into their existing workflows. This meant teams no longer had to write SQL or Python scripts from scratch for each new customer. The entire flow—from raw data ingestion to validated, transformed, dbt‑compatible code—was handled in one platform, cutting integration time from weeks to hours. Lume also provided a dashboard where teams could monitor integration progress, review suggested mappings, and override AI decisions when needed. Its value proposition was particularly strong for SaaS companies, finte