Agentic mesh with native graph and vector data

DigitalKin built an agentic mesh ecosystem on SurrealDB, unifying document, relational, and real-time state with multi-tenant isolation and live updates.

IndustryArtificial intelligence

OutcomeUnified agent memory with multi-tenancy and sync

01 |KEY CHALLENGES

What they needed to solve

The technical and operational hurdles the team faced before adopting SurrealDB.

Multi-tenant isolation

Customer data boundaries required isolation without spinning up separate clusters.

Real-time state

Polling created laggy dashboards and brittle webhook chains across agents.

Schema agility

Fast-moving workflows needed schema-optional modelling without bottlenecks.

Path to graph data

The team needed an upgrade path to graph relationships without a rewrite.

02 |SOLUTIONS

How SurrealDB helped

The architecture decisions and SurrealDB capabilities that addressed each challenge.

Agentic mesh with graph and vector data

SurrealDB powers search, relationships, and memory with native graph and vector capabilities.

Schema flexibility for turnkey agent data

Provided a database-within-a-database model for agent developers to store data freely.

Live queries for push-based updates

Streamed changes to keep agents and enterprise UIs aligned without polling.

Namespace tenancy and hybrid deployments

Isolated tenants with namespaces and kept parity between cloud and self-hosted nodes.

03 |RESULTS

The impact

Measurable outcomes delivered after moving to SurrealDB.

Simplified multi-tenant stack

Namespace isolation reduced per-tenant overhead while preserving boundaries.

Faster iteration loops

Studio accelerated query design, schema evolution, and debugging.

Real-time experience

Push-driven UX kept the agent mesh and dashboards in sync.

Graph & vector ready

Prepared to consolidate agent memory and knowledge with relationships.

MORE CASE STUDIES

Saks Fifth Avenue uses SurrealDB's vector search and graph capabilities to deliver real-time, AI-powered personalisation across 5 million luxury customers and 45 million monthly product-recommendation queries.

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