Why a graph instead of a vector database?

Vectors are good at “text like this.” Graphs are good at “this is connected to that.” Agents that must not invent relationships need both, and we put Neo4j on the relationship side.

Do you also implement Cognee?

Yes. Cognee is often the memory API the agent talks to; Neo4j is the graph store underneath. We will tell you if you need one or both.

Can the graph stay in our cloud?

Yes. Aura or self-hosted, with the same residency rules as the rest of the stack.

Salesforce MVP Hall of Fame · Certified Partner since 2010

Graph memory for agents that need to know how things relate.

Vector search finds similar text. It does not know that this clause belongs to that vendor, or that this patient is on that pathway. We implement Neo4j as the relationship layer under Claude, Gemini, or OpenAI — GraphRAG, not another pile of chunks. The first week is in the org, reading what already exists.

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01Models · Claude, Gemini, OpenAI, Bedrock
02Agents · Agentforce, CrewAI, ADK, A2A
03Memory · Neo4j, Cognee, RAG
04Identity · IndyKite, SSO, entitlements
05Governance · policy, audit, human override

01 · MODELS

02 · AGENTS

03 · MEMORY

04 · IDENTITY

05 · GOVERNANCE

Hover to separate the layers

What we put in

The work on this layer.

The honest no: if the work is a software factory with a named delivery date, we are the wrong partner.

01Graph model for the domain you care about — legal, CRM, supply chain, or collectionsGraph model for the domain you care about — legal, CRM, supply chain, or collections

02Ingestion from Salesforce, documents, and existing warehousesIngestion from Salesforce, documents, and existing warehouses

03Query patterns and MCP tools so agents can ask the graph safelyQuery patterns and MCP tools so agents can ask the graph safely

04A split of duties with Cognee when you want an opinionated memory layer on topA split of duties with Cognee when you want an opinionated memory layer on top

Use cases

Where this shows up in the work.

These are the use cases we usually pair with Neo4j.

Legal document review

Contracts as a desk. Review, redline, and a lawyer on the exceptions. We will not invent a 209% ROI.

CLO

Contract management

Contract lifecycle as a desk. Intake, review, and a lawyer on the exception. Not a $2.2M breach slide.

Legal Operations Manager

Data analytics

A view on records the org already trusts. Tableau or the CRM report after the duplicates are gone.

CDO

Questions

What we actually say.

Why a graph instead of a vector database?: Vectors are good at “text like this.” Graphs are good at “this is connected to that.” Agents that must not invent relationships need both, and we put Neo4j on the relationship side.
Do you also implement Cognee?: Yes. Cognee is often the memory API the agent talks to; Neo4j is the graph store underneath. We will tell you if you need one or both.
Can the graph stay in our cloud?: Yes. Aura or self-hosted, with the same residency rules as the rest of the stack.

The brief

Agents guessing at relationships they should know?

We will sketch the graph for one domain and tell you whether Neo4j, Cognee, or both belong in the build.