Introducing Iceberg DB: India's Serverless Vector Database & AI Agent Memory Engine (<20ms Latency)

While building RAG pipelines and autonomous AI agents in India, I kept hitting the same three walls with US-hosted vector databases:

Today, I'm excited to launch Iceberg DB — a serverless vector database and cognitive memory platform hosted in Mumbai ( ap-south-1 ).

All 5 official SDKs are live on global package registries today:

from iceberg import Client client = Client ( api_key = " ib_your_key " ) # 1. Create a collection & index raw text (embeddings generated automatically) client. create_collection ( " my_docs " ) client. index_text ( " my_docs ", " Iceberg DB is hosted in Mumbai with sub-20ms latency. " ) # 2.

Hybrid Search (Dense + BM25) results = client. search ( " my_docs ", " where is Iceberg hosted? ", search_type = " hybrid " ) for r in results: print ( f " { r. score:. 2 f } — { r. text } " ) # 3.

Persistent Agent Memory client. memory. remember ( " agent_01 ", " User prefers concise Python code ", memory_type = " long_term " ) memories = client. memory. recall ( " agent_01 ", " how should I format answers? " ) Enter fullscreen mode Exit fullscreen mode 🔗 Try It Live Website & Interactive Search Demo: https://icebergdb.in Cloud Console (Get Free API Key in 30s): https://dashboard.icebergdb.in/signup Documentation: https://icebergdb.in/docs Interactive API Playground: https://api.icebergdb.in/docs I'd love for you to test it out and share your feedback!