When moving to a new collection management system, data migration is often complex and time-consuming. Fields do not always map one-to-one, terminology differs and information has often been recorded in different ways over time. This creates a risk that context is lost or data is migrated incompletely. With this application, we help analyse existing data structures and carefully align fields between old and new systems, creating a better basis for migration while preserving coherence, meaning and usability.

We help support data migration between legacy collection systems and new Collection Management Systems by aligning fields, values and data structures. We map which information belongs where, how different field types relate to each other and where conversion, normalisation or enrichment is needed. Existing data is better prepared for migration and the risk of losing context, inconsistencies or incomplete transfer is reduced. The result is a cleaner, better-structured and future-proof dataset that fits the requirements of a new system.

Control and quality

AI does the preparatory work. Results remain reviewable and are configured around your sources, fields, terminology and quality criteria. Where relevant, the source or passage remains traceable. Your organisation decides what is adjusted, approved and ultimately used.

A concrete first step

We prefer to start with a clearly defined test set. Together we agree the required output, quality criteria and review flow. This shows what works before you scale up.

Migration

Control and quality

A concrete first step