Graph Database for LLM Agents

A managed graph database service (like Supabase but for graphs) optimized for LLM agents and AI applications. Simplifies storing and querying relational data that AI models need to reason over.

Graph databases are having a genuine moment because multi-agent LLM architectures require storing entities and relationships in ways that relational databases handle awkwardly — and the explosion of agent frameworks like LangGraph and AutoGen has created real developer demand for persistence layers that model knowledge graphs natively. Neo4j is the obvious incumbent, but it's an enterprise product with enterprise pricing and no managed, developer-friendly onboarding story aimed at AI workloads, which is exactly the gap Supabase exploited in relational databases. The $5k–$50k/mo revenue band is plausible for a usage-based managed service with a generous free tier to drive adoption, though it implies staying small or finding a wedge into teams with serious data volumes before hitting the ceiling. The biggest risk is commoditization: vector database players like Weaviate and Qdrant are already adding graph-like traversal features, and if the major cloud providers ship native graph-plus-vector managed services, the addressable wedge collapses fast.