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Welcome to the Lume documentation guide. Follow the instructions below to learn how to generate mapping logic, review your mappings, and deploy them for production use.

What is Lume?

Lume automates data mappings using AI. With Lume, you can use AI to automatically generate mapping logic to move data between any two schemas. This allows you normalize data, ingest client data, and create your data pipelines 10x faster by mapping data in minutes, rather than days, weeks, or months.

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Never spend time manually mapping data again

Our mission

We are on a mission to automate the painstakingly manual process of data mapping, after experiencing this frustration as engineers ourselves.

The usual mapping process involves a labor-intensive cycle: analyzing data to determine what’s relevant, selecting the appropriate properties, developing the mapping logic, and constantly updating mappers to accommodate schema changes in source or target systems. This process takes days, weeks, or even months for most teams, and automating it has traditionally been borderline impossible due to unique differences in data.

The magic of Lume

Lume is a comprehensive AI engine, with multiple AI and deterministic modules working together to automate your data mapping tasks. Lume is driven by sentiment understanding:

  • Lume understands your source and target schemas in a semantic level, which allows it to discern relationships between target properties and relevant source properties.
  • With this understanding, Lume generates mapping logic to map any source data to your target schema.
  • Importantly, Lume does not generate data, but rather generates logic that is then executed deterministically. This is crucial when using AI to map mission-critical data, as Lume’s data outputs will be a product of source data, rather than generated.

Use Cases

Ingest client data

Each client you work with handles data differently. They name, format, and handle their data in their own way, and it means you have to iteratively ingest each new client’s data.Lume AI solves this by allowing you to handle all client data as one. Normalize it in seconds.

Normalize data from unique data systems

To provide your business value, your team needs to connect to various data providers or handle legacy data. Creating pipelines from each one is time consuming, and things as small as column name differences between systems makes it burdensome to get started.Lume AI solves this  by gaining an understanding of the data, discerning the differences between all your integrated systems, and automatically mapping it to your desired format.

Build and maintain data pipelines

Creating different pipelines to your target models, whether for BI tooling, downstream data processing, or other purposes, means you have to manually create and maintain these mappings between models.Lume AI not only creates these mappings automatically, but maintains them by recognizing changes in the models and remapping them.