Industries

Connected-data problems, by sector.

The traversal shapes are the same everywhere; what changes is which one you reach for first. Three sectors, and where a graph earns its keep in each.

Fintech

Transaction networks, fraud rings and beneficial-ownership chains are graphs. Query them as graphs, with per-tenant isolation and one predictable price per instance.

Explore Fintech

SaaS

Ship a graph feature per tenant without running a cluster per tenant. Real database isolation, sizes from 512 MB up, billed for what you use.

Explore SaaS

Healthcare

Referral networks, care pathways and research context graphs: connected data problems in an industry made of them.

Explore Healthcare

Not listed?

The pattern travels further than three sectors.

Logistics dependency graphs, telecom networks, publishing knowledge bases. If the interesting question is 'what connects to what', the shape is the same. Browse the solutions to find the one that matches your workload.

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~98.7%

token efficiency at 3,700 entities (see the footnotes above)

Put your first graph up in a minute.

A free instance takes about a minute and no card. Write two MERGE statements, read them back, and you have a living graph, with provenance on every fact.

Start free View the quickstart

First-graph path

Live

  1. Create a free instance

    No card. Ready in about a minute.

  2. Connect your driver

    bolt+s:// URI into the driver you already use.

  3. Write two MERGEs

    That's the entire shape of agent memory.

  4. Point an agent at it

    One MCP config block. No integration code.