Vector Search
Disconnected data chunks.
- No relationships preserved
- Hallucinations & shallow answers
- Context is lost at retrieval
v0 · 2026
/
Knowledge Graph Platform for Enterprise AI
Stop Guessing.
Start Connecting.
The Graph-Native Analytics Engine for Enterprise AI.
Move beyond vector search. GraphEdge Analytics uses advanced Knowledge Graphs and GraphRAG to deliver explainable, accurate, and scalable insights from your most complex data.
BUILT ON
Neo4j Aura
·
GraphRAG
·
AWS
·
Vector + Graph Hybrid
·
Cypher / SPARQL
01 / The Problem
Your Data is Connected.
Your Data is Connected.
Your Insights Should Be, Too.
Traditional vector search often loses context, leading to "hallucinations" or shallow answers. GraphEdge captures the relationships between your entities—people, processes, and products—to provide the full business context AI needs to be truly intelligent.
GraphEdge
A structured, interconnected network of knowledge.
- Relationships as first-class context
- Explainable, traceable answers
- Synthesis across the entire graph
02 / The Platform
An analytics engine built on relationships.
01
GraphRAG Powered
We don't just retrieve text; we traverse relationships to find deep, synthesis-level answers.
02
Explainable AI
Stop trusting black boxes. Our knowledge graphs provide the "provenance" for every AI-generated insight.
03
Enterprise-Ready Scalability
Built on a production-grade infrastructure (Neo4j Aura) to handle your growth from MVP to global scale.
03 / Use Cases
Where relationships become revenue.
Finance
CASE_01
Financial Integrity
Detect fraud rings by analyzing transactional flows, not just single transactions.
detects
ring patterns
Operations
CASE_02
Operational Intelligence
Map your entire supply chain to identify bottlenecks before they happen.
predicts
bottlenecks
CX
CASE_03
Customer 360
Link every interaction across your enterprise to deliver hyper-personalized experiences.
unifies
every touch
04 / How it works
From raw data to graph-native answers.
-
01 Ingest
Connect your data sources.
SQL, NoSQL, APIs, document stores, data lakes — GraphEdge ingests structured and unstructured data from wherever it lives.
PostgresMongoDBS3RESTKafkaSnowflake -
02 Model
We build your Knowledge Graph automatically.
Our engine extracts entities, resolves identities, infers relationships, and materializes a dynamic graph tuned to your business context.
Entity ResolutionSchema InferenceGraph Embeddings -
03 Ask
Query in natural language.
Business users ask questions in plain English. GraphRAG traverses the graph, returns high-fidelity answers — with the exact paths that produced them.
NL → CypherGraphRAGProvenance Trails
05 / Get in touch
Let's map your knowledge graph.
Tell us about your data and the questions you wish you could ask it. We'll show you what a graph-native approach looks like for your team.
GENERAL
info@graphedgeanalytics.com
FOUNDER
smaitra1@graphedgeanalytics.com
STATUS
Final stage of development · Preparing for launch