Neo Graphs transforms your existing data model into a production-ready Neo4j graph database — complete with AI-optimized traversals, relationship intelligence, and knowledge graph infrastructure. No rewrites. No migration risk. Minutes, not months.
// Define your entities — any data model, any industry { "projectName": "YourProject", "entities": [ { "entity": "Customer", "fields": "string Name, string Email, Region Region, Segment Segment, decimal LifetimeValue" }, { "entity": "Product", "fields": "string Name, string SKU, Category Category, |Order,Review" }, { "entity": "Order", "fields": "Customer Customer, Product Product, DateTime OrderDate, decimal Total" } ] }
// sample-queries.cypher (auto-generated) // Impact analysis: everything connected to a Customer MATCH (n:Customer { SqlId: $sqlId })-[*1..2]-(connected) RETURN DISTINCT labels(connected)[0] AS Type, connected.Name AS Name; // Shortest path between any two entities MATCH (a { SqlId: $startId }), (b { SqlId: $endId }), p = shortestPath((a)-[*..15]-(b)) RETURN p; // Hierarchy traversal (org charts, categories) MATCH path = (n:Category { SqlId: $id }) -[:HAS_PARENT*1..10]->(ancestor) RETURN [n IN nodes(path) | n.Name] AS chain; // Data quality: orphan nodes MATCH (n:Product) WHERE NOT (n)--() RETURN n;
// Schema/schema.cypher (auto-generated) CREATE CONSTRAINT customer_sqlid_unique IF NOT EXISTS FOR (n:Customer) REQUIRE n.SqlId IS UNIQUE; CREATE INDEX customer_name_idx IF NOT EXISTS FOR (n:Customer) ON (n.Name); // GraphQueryRepository.cs (auto-generated) public async Task<IEnumerable<HierarchyNode>> GetCategoryAncestorsAsync(long sqlId) { await using var session = _driver.AsyncSession(); return await session.ExecuteReadAsync(...); }
// TypeScript client (auto-generated) export interface CustomerNode { sqlId: number; name: string; email: string; lifetimeValue: number; regionId: number; segmentId: number; } export const customerApi = { getAll: () => fetch('/api/graph/customer') .then(r => r.json()), getImpact: (id: number, hops = 2) => fetch(`/api/graph/customer/${id}/impact?hops=${hops}`) .then(r => r.json()), getShortestPath: (from: number, to: number) => fetch(`/api/graph/path/${from}/${to}`) .then(r => r.json()) };
// YourProject-graphdb.zip (95 files) Nodes/ CustomerNode.cs, ProductNode.cs … Repositories/ ICustomerGraphRepository.cs … Controllers/ CustomerGraphController.cs … Sync/ CustomerGraphSyncService.cs … Schema/ schema.cypher, GraphSchemaInitializer.cs Queries/ sample-queries.cypher ← NEW GraphQueryRepository.cs ← NEW Seed/ SeedOrder.cs, GraphSeeder.cs Insights/ GraphInsightsRepository.cs TypeScript/ models.ts, graphApiClient.ts Diagrams/ er-diagram.md, graph-model.dot Neo4jNative/ docker-compose.yml, import.ps1 Swagger/ openapi.json Postman/ collection.json RUN-REPORT.html
Relational databases store data in rows and columns. AI, recommendations, fraud detection, and knowledge graphs need relationships. Graph databases make those relationships first-class — but building the graph layer manually takes months. Neo Graphs does it in seconds.
Graph queries are the backbone of RAG retrieval, recommendation engines, and LLM-powered knowledge systems. Neo Graphs generates traversal-ready infrastructure your AI stack can plug into immediately.
SQL JOINs degrade exponentially with depth. Graph traversals stay constant. Impact analysis, shortest-path, and hierarchy walks that take seconds in Neo4j would take minutes (or fail) in SQL.
Keep your relational database exactly as-is. Neo Graphs generates a graph layer alongside it — synchronized via MERGE-based sync services. No migration risk, no data loss, fully reversible.
Answer "what depends on this?" in milliseconds. When a product changes, a user is flagged, or a server goes down — graph traversal finds every connected entity instantly.
Your entity model is already a knowledge graph waiting to be expressed. Neo Graphs generates the schema, constraints, indexes, and query repository that turn your data into queryable knowledge.
Hand-building a graph layer for 50+ entities takes a team weeks. Neo Graphs generates the entire stack — models, APIs, queries, sync, schema, diagrams — in one deterministic pass under 3 seconds.
Every generation produces a coherent, tested set of 15 component types — plus auto-generated queries, demo data, and a run report.
Typed node models with a SQL sync key. Async Cypher repositories with CRUD, relationship links, and collection traversals.
Ready-to-deploy controllers with OpenAPI metadata and Swagger documentation. Call from any language or framework.
MERGE-based sync services that mirror your writes into Neo4j in real time. Your graph never drifts from your source of truth.
250+ lines of model-aware Cypher: per-entity CRUD, hierarchy walks, impact analysis, shortest path, orphan detection, and data quality checks.
10 realistic rows per entity with context-aware typing (names get names, emails get emails) and all relationships wired — instant visualization.
Docker Compose + neo4j-admin import scripts + CSV headers. Stand up a live Neo4j instance from your model in one command.
Typed interfaces and a framework-agnostic fetch client matching the generated REST API. Works with React, Angular, Vue, or Node.
Mermaid ER, GraphViz DOT, architecture diagrams, and a self-contained HTML run report with component drill-down and next steps.
Works with any relational schema — ERP, CRM, e-commerce, healthcare, fintech, logistics, or any domain.
Use the web form, upload an Excel sheet, or POST a JSON model. Define fields, foreign keys, and relationships — Neo Graphs understands your model regardless of industry or scale.
Pre-flight validation catches issues before any code is written. Valid models produce the complete graph layer — queries, schema, APIs, sync services, diagrams — in one deterministic pass.
Download the ZIP, deploy the native import bundle, or connect directly to a running Neo4j instance. Seed demo data, run the generated queries, and see your graph come alive.
Anywhere relationships matter, Neo Graphs accelerates your graph journey.
Patient pathways, drug interactions, care team networks, referral chains — graph traversals that power clinical decision support and AI diagnostics.
Fraud detection, anti-money laundering, risk propagation, counterparty analysis — sub-second relationship queries on complex transaction networks.
Product recommendations, customer journey graphs, supply chain visibility, inventory dependencies — graph-powered personalization at scale.
Bill-of-materials explosions, supply chain impact, route optimization, equipment dependency trees — operational intelligence from relationships.
Org charts, approval chains, asset dependencies, compliance mappings — the relationships your ERP stores as foreign keys, surfaced as traversable graphs.
RAG retrieval, entity linking, ontology mapping, semantic search — the knowledge graph infrastructure your LLM pipeline needs, generated from your existing schema.
Quick answers — the full FAQ has everything else.
Yes. Neo Graphs reads your entity structure from a web form, Excel sheet, JSON model, or live SQL database. It generates a graph layer alongside your existing schema — nothing is modified or migrated. Your source database continues as-is.
Generated code includes C# (repositories, APIs, sync services), TypeScript (client models + API wrapper), Cypher (schema, queries, constraints), YAML (Docker Compose), and shell scripts (import). The generated graph layer integrates with any stack that can call REST APIs or connect to Neo4j.
Graph databases are the preferred retrieval layer for RAG (Retrieval-Augmented Generation) because they preserve relationships that flat vector stores lose. Neo Graphs generates the knowledge graph infrastructure — schema, traversal queries, and API endpoints — your LLM pipeline needs to retrieve context-rich, relationship-aware results.
Yes — sign up with Google and get up to 5 free generation runs with a total of 20 entities (use them all in one run or spread across multiple). The sandbox (no signup) lets you explore the full output using a sample model. See all plans →
Sign in and generate your first graph layer free. Or explore the sandbox — no account needed.