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What does it do?

  • Data Mapping
  • Data Integration
  • Data Normalization
  • Data Pipeline Management
  • Data Transformation

How is it used?

  • Use web app or API
  • automate data mapping and normalization.
  • 1. Access web platform
  • 2. Ingest data
  • 3. Build pipelines
See more

Who is it good for?

  • Data Scientists
  • IT Professionals
  • Business Intelligence Analysts
  • Data Engineers
  • Data-Driven Enterprises

Details & Features

  • Made By

    Lume
  • Released On

    2023-08-27

Lume AI is a cutting-edge platform designed to revolutionize data mapping and management through the power of artificial intelligence. It offers a comprehensive suite of features that streamline the process of integrating, normalizing, and managing data across various systems, making it an invaluable tool for businesses dealing with complex data environments.

Features:
- AI-Powered Data Mapping:
- Automatic Mapping Logic: Automatically generates mapping logic to move data between any two schemas, significantly reducing the time and effort required for data integration.
- Data Normalization: Normalizes messy data from different systems, ensuring consistency and accuracy across all data sources.
- Complex Data Handling: Handles complex data mappings with ease, enabling teams to transform data efficiently using AI.

- Data Pipeline Management:
- Pipeline Building: Enables users to build hundreds of data pipelines quickly, reading from and writing to any source and destination models.
- Auto-Maintenance: Detects changes in source data or target models and automatically re-transforms the data to adapt to new models, ensuring continuous data flow without manual intervention.

- Deployment and Review:
- Mapper Deployment: Allows users to save and deploy mappers to use on new data, enabling confident and deterministic future data mapping.
- Visibility and Management: Provides comprehensive visibility and management over all data pipelines and mappings, enabling users to review, edit, and deploy data mappers in seconds.

- Security:
- SOC 2 Compliance: Built with security as a top priority, being SOC2 Type-1 and Type-2 certified, ensuring that data handling meets high security standards.

How It Works:

Lume AI operates primarily through its web-based platform and API, allowing users to integrate AI-powered data mapping into their existing systems. The process involves:

1. Data Ingestion: Users can onboard more customers and partners faster by ingesting their unique data in seconds.
2. Data Mapping: The AI automatically generates mapping logic to move data between schemas, normalizing and transforming it as needed.
3. Pipeline Management: Users can build and manage data pipelines, with the platform automatically maintaining and adapting to changes in data models.
4. Deployment: Mappers can be reviewed, edited, and deployed quickly, ensuring seamless data integration and management.

Integrations:

Lume AI supports integration with various data systems, allowing for seamless data flow between different platforms. This includes:
- Data Sources and Destinations: The platform can read from and write to any source and destination models, making it highly versatile.
- CI/CD Workflows: Integrates smoothly with existing CI/CD pipelines.

Availability and User Base:

Lume AI is available as a web app and API, providing multiple access points for users. It was released in 2024 and is designed for businesses and organizations that need to manage large volumes of complex data efficiently. The platform is not open source, ensuring proprietary technology and security measures are maintained.

Lume AI is ideal for data engineers, data scientists, and IT professionals who require robust and automated data mapping solutions. Its AI-driven approach makes it particularly useful for companies looking to scale their data operations and improve data consistency across various systems.

  • Supported ecosystems
    Unknown
  • What does it do?
    Data Mapping, Data Integration, Data Normalization, Data Pipeline Management, Data Transformation
  • Who is it good for?
    Data Scientists, IT Professionals, Business Intelligence Analysts, Data Engineers, Data-Driven Enterprises

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