The Lifter: Agentic AI-Powered Data Migration & Modernization Platform

Problem - Enterprise data is often distributed across legacy databases, applications , and modern cloud platforms. As organizations modernize their technology landscape, migrating this data becomes a complex, time-consuming, and risk-prone activity. Migration teams typically spend significant effort understanding legacy structures, identifying dependencies, profiling data, creating source-to-target mappings, developing transformation logic, documenting undocumented environments, and validating migrated data. These activities are frequently dependent on manual analysis, spreadsheets, specialized skills, and tribal knowledge. The result is longer migration timelines, higher costs, increased dependency on scarce technical expertise, and greater risk of data quality issues or migration failures.

Solution - Data Lifter is an AI-powered data migration and modernization solution designed to accelerate the journey from legacy data environments to modern data platforms. It automates and assists with key stages of the migration lifecycle, including data discovery, profiling, legacy understanding, source-to-target mapping, transformation, documentation, and migration validation. Data Lifter helps teams understand what exists in the current environment, determine how data should move to the target environment, identify potential migration challenges, and validate whether the migrated data meets expectations. It can support scenarios such as database migration, cloud migration, database modernization, legacy modernization, and migration to modern analytics and data platforms.

Key Features -

1. Data Discovery & Profiling -Automatically analyse source data structures, schemas, tables, columns, relationships, dependencies, and data characteristics to establish a clear view of the existing environment.
2. Legacy Understanding - Use AI-assisted analysis to interpret legacy data structures and generate useful technical documentation, reducing reliance on undocumented knowledge and individual experts.
3. Automated Data Mapping -Accelerate source-to-target analysis by identifying corresponding data elements and generating initial mapping recommendations between legacy and target environments.
4. Transformation Support - Assist migration teams in defining and implementing data transformation rules required when moving between different schemas, databases, technologies, or platforms.
5. Migration Assistance - Support modernization initiatives by helping teams move data from legacy technologies into modern databases, cloud platforms, lakehouses, and analytics environments.
6. Migration Validation - Compare source and target data to identify missing records, mismatches, transformation issues, and other discrepancies, improving confidence in migration outcomes.
7. Documentation Generation - Generate migration-ready documentation covering schemas, mappings, dependencies, transformation logic, and other relevant technical information.
8. Migration Insights & Risk Identification - Surface potential data quality, compatibility, dependency, and transformation challenges early so teams can address risks before they impact migration execution.

Key technical capabilities include: • AI powered schema and metadata understanding • Automated source to target data mapping • Data profiling and relationship discovery • AI assisted transformation logic generation • Legacy documentation and knowledge extraction • Data comparison and migration validation • Dependency and migration-impact analysis • Extensible support for additional source and target technologies

AWS Services Used - EC2, ECR, ECS , Bedrock, Amazon RDS, AWS Redshift, AWS Secretmanager