MING (Formerly Vector Migration) is the world’s first Vector Database Migration Platform.

You can now seamlessly transfer your vector data between leading vector DBs like Qdrant, Weaviate, Pinecone, Milvus, Mongo DB and more.

Modern AI applications rely heavily on vector databases to support semantic search, recommendation engines, and retrieval-augmented generation (RAG) systems. As these applications scale, organisations often find that their initial vector database choice no longer satisfies evolving performance, cost, or deployment needs.

This is where vector migration becomes essential, not as a one-time task, but as a core capability within a growing AI infrastructure.

Unlike traditional database migrations, vector migration must consider similarity search behaviour, metadata filtering, and indexing differences across platforms. A successful migration ensures that search relevance, latency, and application logic remain consistent after the transition. MING is a purpose-built tool designed to address these challenges safely and efficiently.

At a high level, the tool enables teams to:

• Migrate vector embeddings between databases
• Preserve metadata, IDs, and structural consistency
• Avoid unnecessary re-embedding where possible
• Reduce downtime during production migrations
• Execute repeatable, predictable migrations

The platform is designed for AI developers, data engineers, and ML researchers who need reliable infrastructure transitions without disrupting live systems.

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