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database.ai is for sale
I bought database.ai as a brand for a startup idea. I’d like to sell at fair market price to someone who can make better use. Buy it now for US $1,250,000. Or make an offer. Direct message Mark on LinkedIn to inquire — DMs are open.
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Database is still the load-bearing noun in the agent stack: models may reason, but their context, memory, retrieval, and operational records all terminate in databases.
Infrastructure The agent stack now has a standard protocol for reaching databases and other systems of record
Platform Major data platforms now treat vector retrieval as a database feature, not an external bolt-on
Open Stack Postgres also absorbed vector search, reinforcing database as the category word
Infrastructure
The agent stack now has a standard protocol for reaching databases and other systems of record
Anthropic's MCP launch defined the problem directly: AI assistants need a standard way to connect to the systems where data lives. By December 9, 2025, Anthropic said the ecosystem had grown to more than 10000 active public servers.
Agent workflows can change quickly; the database layer they connect to is the durable part.
Platform
Major data platforms now treat vector retrieval as a database feature, not an external bolt-on
Databricks Vector Search is built into the Data Intelligence Platform, supports hybrid keyword-similarity search, and scales past one billion vectors on storage-optimized endpoints. MongoDB Atlas Vector Search lets teams search vector data alongside operational data and explicitly positions the feature for RAG and agentic systems.
Open Stack
Postgres also absorbed vector search, reinforcing database as the category word
PostgreSQL's pgvector release note is the cleanest marker that even open-source Postgres absorbed vector similarity search into its extension ecosystem. The result is that the word database now covers transactional records, text retrieval, and embedding search in one operational surface.
Context for database.ai
MCP
Vector Search
pgvector
MCP exists because AI systems need a standard way to reach the systems where data lives. That framing makes the database layer explicit rather than implicit.
Databricks Vector Search treats retrieval as a governed platform capability, not a separate niche service. The word the platform still uses is database.
pgvector made vector similarity search a normal Postgres extension instead of a separate database purchase. That matters because it collapsed AI retrieval back into the incumbent system of record.