• Vector Storage & Indexing: Save embeddings from any AI model and organize them for fast retrieval.
• Semantic Search: Perform similarity searches and nearest-neighbor queries across millions of vectors.
• Scalable Infrastructure: Easily scale your Qdrant instance to handle growing datasets.
• Integration Ready: Connect with Python, Node.js, or any REST/GRPC-compatible application.
• Real-Time Updates: Insert, update, or delete vectors without downtime for continuous operation.
• Custom Filtering & Metadata: Add metadata to vectors and filter queries for precise results.

• One-Click Deployment: Launch a fully configured Qdrant instance in minutes.
• Hosted in Türkiye: Keep your AI and vector data under national data protection standards.
• Secure & Reliable: SSL, automated backups, and isolated cloud environment.
• High Performance: Optimized infrastructure ensures low-latency queries even for large datasets.
• Automatic Updates: Stay current with the latest Qdrant features, improvements, and security patches.
• Local Expert Support: Get guidance from engineers experienced in AI, vector databases, and cloud deployment.

• Qdrant v2.x (latest stable)
• Debian 12 (Bookworm)
• Systemd-managed service
• amd64 architecture
• cloud.core.gen.tr image template
• License: Apache 2.0

Stop juggling multiple AI tools and scattered data.
With Qdrant on cloud.core.gen.tr, you own your embeddings, indexes, and search pipelines — all in a secure, high-performance cloud environment.

Vector search isn’t just about storing data — it’s about powering intelligent applications. Make every query count.