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Luis Salvador
Sales Engineer
1
© 2024 Neo4j, Inc. All rights reserved.
New features in Neo4j and roadmap
Knowledge Graphs + LLM = 😁
2
© 2024 Neo4j, Inc. All rights reserved.
• Parallel Runtime for faster analytical Queries
• Change Data Capture better data integration
• Autonomous clustering and Fabric for limitless scalability
• Graph Schema, Improved Backup recovery, incremental
import
• Neo4j Ops Manager for managing databases
• Aura Enterprise Database on all clouds (AWS, GCP, Azure)
• SOC II Type 2 compliance, AuraDB APIs, RBAC
configuration
• Better observability with security log forwarding
Performance metrics forwarding (EAP)
• Private Link & CMEK (Coming soon)
Neo4j product capabilities launched in 2023
Neo4j Inc. All rights reserved 20244
4
• Unified Developer Experience with Workspace
• Self-service Data Import
• GraphQL Support & Simplified Drivers API
• Bloom support for GDS algorithms
• GDS Python API
• Knowledge Graph Embeddings
• Longest Path & Topological Sort Algorithm
• Vector Search
• Real Time integration with Embedding APIs & LLM
Models
• Cloud Integrations (OpenAI + MS Azure OpenAI,
VertexAI, AWS Bedrock, Langchain, LlamaIndex)
Graph Schema: New constraints on
nodes, relationships and properties:
• Unique relationship property
• Relationship key
• Property data types
NEO4J 5.x NEW CAPABILITIES
Database Enhancements
Neo4j Inc. All rights reserved 20244
5
Graph Pattern Matching: Improved
expressivity of graph navigation with
quantified path patterns,
a more powerful and performant
syntax to navigate and traverse your
graph.
NEO4J 5.x NEW CAPABILITIES
Database Enhancements
Neo4j Inc. All rights reserved 20244
6
NEO4J 5.x NEW CAPABILITIES
Database Enhancements
Graph Pattern Matching Example → Fraud Rings
Neo4j Inc. All rights reserved 20244
7
QPP
MATCH path=(a:Account)-[:PERFORMS]->(first_tx)
((tx_i)-[:BENEFITS_TO]->(a_i)-[:PERFORMS]->(tx_j)
WHERE tx_i.date < tx_j.date
AND 0.80 <= tx_i.amount / tx_j.amount <= 1.00
){3,6}
(last_tx)-[:BENEFITS_TO]->(a)
WHERE size(apoc.coll.toSet([a]+a_i)) = size([a]+a_i)
RETURN path
NEO4J 5.x NEW CAPABILITIES
Parallel Runtime: Speed up analytical query up to 100x
Neo4j Inc. All rights reserved 20244
8
Parallel Runtime Speedup
Up to 100x faster analytical queries by adding CPU
cores
Neo4j Inc. All rights reserved 20244
9
More cores
Faster
Queries
NEO4J 5.x NEW CAPABILITIES
Change Data Capture: Automated Real-Time
Change Tracking
Neo4j Inc. All rights reserved 20244
10
© 2023 Neo4j, Inc. All rights reserved. 11
Vector embeddings
12
● Same concepts, just “an arrow”
● 100s or 1000s dimensions
● Each dimension corresponds to an
interesting feature or characteristic
king − man + woman ≈ queen
1 2 3
13
© 2024 Neo4j, Inc. All rights reserved.
NEO4J 5.x NEW CAPABILITIES
Fabric Auto-Sharding
Neo4j Inc. All rights reserved 20244
15
Coming 2024+
Mapping
Sharding
Rules
© 2024 Neo4j, Inc. All rights reserved. 16
Neo4j Inc. All rights reserved 2024
17
94%of business
leaders agree that AI is
critical to success over
the next five years1
1. Deloitte’s State of AI in the Enterprise
18
© 2024 Neo4j, Inc. All rights reserved.
● Lack of enterprise domain knowledge
● Inability to verify answers
● Hallucination
● Ethical and data bias concerns
19
Ground LLMs in Neo4j’s Knowledge Graph
20 Neo4j Inc. All rights reserved 2024
20
Why RAG With Vector Databases Fall Short
Similarity is insufficient for rich enterprise reasoning
Neo4j Inc. All rights reserved 2024
21
1
3
2
4
Only leverage a fraction of
your data: Beyond simple
“metadata”, vector databases
alone fail to capture
relationships from structured
data
Miss critical context: Struggle
to capture connections across
nuanced facts, making it
challenging to answer multi-
step, domain-specific,
questions
Vector Similarity ≠ Relevance:
Vector search uses an incomplete
measure of similarity. Relying on it
solely can result in irrelevant and
duplicative results
Lack explainability:
The black-box nature of
vectors lacks transparency
and explainability
22
What is a Knowledge Graph?
An information architecture with layered connections.
Neo4j Inc. All rights reserved 20244
DATA INFORMATION KNOWLEDGE INSIGHT MEANING
records sets relationships patterns layers
Neo4j Inc. All rights reserved 2024
23
Knowledge Graphs + LLMs
23
Facts
Explicit
Explainable
Words
Implicit
Opaque
KGs LLMs
+
RAG with Neo4j
Neo4j Inc. All rights reserved 20244
24
Find similar documents,
content and data
Expanded context for related
information and ranking
results
Improve GenAI inferences and
insights. Discover new
relationships and entities
Unified search, knowledge graph and data science capabilities to
improve RAG quality and effectiveness
Vector Search,
Full-text Search,
Geospatial, Pattern
match
Data Science
Knowledge Graph
25
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
Neo4j Inc. All rights reserved 2024
26
Knowledge Graph
Construction with
Cypher Templates
Human
27
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
2 RAG-based Chat Applications
Neo4j Inc. All rights reserved 2024
28
Natural Language
Search combining
explicit and implicit
relationships
Application Human
29
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
2 RAG-based Chat Applications
3 RAG-enhanced General Applications
Neo4j Inc. All rights reserved 2024
30
Natural Language
assistants and co-
pilots,
rooted in business
policy
Prompt +
Relevant
Information
Embedding API LLM API
User
Database
Search
Prompt Response
Relevant Results
Knowledge
Graph
Application
• Integrate Neo4j with leading LLM
open-source frameworks such as
LangChain and LlamaIndex
• Call LLM APIs natively via Cypher using
our open-source APOC library
• Agnostic LLM orchestration connecting
graphs to OpenAI, AWS Bedrock, GCP
Vertex AI, Azure, Anthropic, Hugging
Face, and other proprietary and open-
source foundation models
Integrate with the GenAI Ecosystem
Neo4j Inc. All rights reserved 2024
31
GenAI Stack
Application
Generative AI & Embedding Models
Orchestration
Grounding Knowledge Graph
Neo4jGraph
Neo4jVector
GraphCypherQAChain
n
Neo4jGraphStore
Neo4jVectorStore
KnowledgeGraphIndex
Neo4j GenAI Integrations
Text | Chat | Embedding
NL Query | Image Gen
Neo4j Drivers
Java
Python JavaScript
• Co-Pilot in Neo4j Browser for
autocomplete & Cypher generation
• Bloom & NeoDash NL integration
• More framework integrations:
• Langchain, LlamaIndex,
SemanticKernel, Spring.AI, Haystack
POWERING GENERATIVE AI APPS
Neo4j’s GenAI Roadmap
Neo4j Inc. All rights reserved 2024
32
Coming 2024+
• Parallel Runtime for faster analytical Queries
• Change Data Capture better data integration
• Autonomous clustering and Fabric for limitless scalability
• Graph Schema, Improved Backup recovery, incremental
import
• Neo4j Ops Manager for managing databases
• Aura Enterprise Database on all clouds (AWS, GCP, Azure)
• SOC II Type 2 compliance, AuraDB APIs, RBAC
configuration
• Better observability with security log forwarding
Performance metrics forwarding (EAP)
• Private Link & CMEK (Coming soon)
Neo4j product capabilities launched in 2023
Neo4j Inc. All rights reserved 2024
33
• Unified Developer Experience with Workspace
• Self-service Data Import
• GraphQL Support & Simplified Drivers API
• Bloom support for GDS algorithms
• GDS Python API
• Knowledge Graph Embeddings
• Longest Path & Topological Sort Algorithm
• Vector Search
• Real Time integration with Embedding APIs & LLM
Models
• Cloud Integrations (OpenAI + MS Azure OpenAI,
VertexAI, AWS Bedrock, Langchain, LlamaIndex)
Neo4j Inc. All rights reserved 20244
34

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GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j

  • 2. © 2024 Neo4j, Inc. All rights reserved. New features in Neo4j and roadmap Knowledge Graphs + LLM = 😁 2
  • 3. © 2024 Neo4j, Inc. All rights reserved.
  • 4. • Parallel Runtime for faster analytical Queries • Change Data Capture better data integration • Autonomous clustering and Fabric for limitless scalability • Graph Schema, Improved Backup recovery, incremental import • Neo4j Ops Manager for managing databases • Aura Enterprise Database on all clouds (AWS, GCP, Azure) • SOC II Type 2 compliance, AuraDB APIs, RBAC configuration • Better observability with security log forwarding Performance metrics forwarding (EAP) • Private Link & CMEK (Coming soon) Neo4j product capabilities launched in 2023 Neo4j Inc. All rights reserved 20244 4 • Unified Developer Experience with Workspace • Self-service Data Import • GraphQL Support & Simplified Drivers API • Bloom support for GDS algorithms • GDS Python API • Knowledge Graph Embeddings • Longest Path & Topological Sort Algorithm • Vector Search • Real Time integration with Embedding APIs & LLM Models • Cloud Integrations (OpenAI + MS Azure OpenAI, VertexAI, AWS Bedrock, Langchain, LlamaIndex)
  • 5. Graph Schema: New constraints on nodes, relationships and properties: • Unique relationship property • Relationship key • Property data types NEO4J 5.x NEW CAPABILITIES Database Enhancements Neo4j Inc. All rights reserved 20244 5
  • 6. Graph Pattern Matching: Improved expressivity of graph navigation with quantified path patterns, a more powerful and performant syntax to navigate and traverse your graph. NEO4J 5.x NEW CAPABILITIES Database Enhancements Neo4j Inc. All rights reserved 20244 6
  • 7. NEO4J 5.x NEW CAPABILITIES Database Enhancements Graph Pattern Matching Example → Fraud Rings Neo4j Inc. All rights reserved 20244 7 QPP MATCH path=(a:Account)-[:PERFORMS]->(first_tx) ((tx_i)-[:BENEFITS_TO]->(a_i)-[:PERFORMS]->(tx_j) WHERE tx_i.date < tx_j.date AND 0.80 <= tx_i.amount / tx_j.amount <= 1.00 ){3,6} (last_tx)-[:BENEFITS_TO]->(a) WHERE size(apoc.coll.toSet([a]+a_i)) = size([a]+a_i) RETURN path
  • 8. NEO4J 5.x NEW CAPABILITIES Parallel Runtime: Speed up analytical query up to 100x Neo4j Inc. All rights reserved 20244 8
  • 9. Parallel Runtime Speedup Up to 100x faster analytical queries by adding CPU cores Neo4j Inc. All rights reserved 20244 9 More cores Faster Queries
  • 10. NEO4J 5.x NEW CAPABILITIES Change Data Capture: Automated Real-Time Change Tracking Neo4j Inc. All rights reserved 20244 10
  • 11. © 2023 Neo4j, Inc. All rights reserved. 11
  • 12. Vector embeddings 12 ● Same concepts, just “an arrow” ● 100s or 1000s dimensions ● Each dimension corresponds to an interesting feature or characteristic king − man + woman ≈ queen 1 2 3
  • 13. 13
  • 14. © 2024 Neo4j, Inc. All rights reserved.
  • 15. NEO4J 5.x NEW CAPABILITIES Fabric Auto-Sharding Neo4j Inc. All rights reserved 20244 15 Coming 2024+ Mapping Sharding Rules
  • 16. © 2024 Neo4j, Inc. All rights reserved. 16
  • 17. Neo4j Inc. All rights reserved 2024 17 94%of business leaders agree that AI is critical to success over the next five years1 1. Deloitte’s State of AI in the Enterprise
  • 18. 18
  • 19. © 2024 Neo4j, Inc. All rights reserved. ● Lack of enterprise domain knowledge ● Inability to verify answers ● Hallucination ● Ethical and data bias concerns 19
  • 20. Ground LLMs in Neo4j’s Knowledge Graph 20 Neo4j Inc. All rights reserved 2024 20
  • 21. Why RAG With Vector Databases Fall Short Similarity is insufficient for rich enterprise reasoning Neo4j Inc. All rights reserved 2024 21 1 3 2 4 Only leverage a fraction of your data: Beyond simple “metadata”, vector databases alone fail to capture relationships from structured data Miss critical context: Struggle to capture connections across nuanced facts, making it challenging to answer multi- step, domain-specific, questions Vector Similarity ≠ Relevance: Vector search uses an incomplete measure of similarity. Relying on it solely can result in irrelevant and duplicative results Lack explainability: The black-box nature of vectors lacks transparency and explainability
  • 22. 22 What is a Knowledge Graph? An information architecture with layered connections. Neo4j Inc. All rights reserved 20244 DATA INFORMATION KNOWLEDGE INSIGHT MEANING records sets relationships patterns layers
  • 23. Neo4j Inc. All rights reserved 2024 23 Knowledge Graphs + LLMs 23 Facts Explicit Explainable Words Implicit Opaque KGs LLMs +
  • 24. RAG with Neo4j Neo4j Inc. All rights reserved 20244 24 Find similar documents, content and data Expanded context for related information and ranking results Improve GenAI inferences and insights. Discover new relationships and entities Unified search, knowledge graph and data science capabilities to improve RAG quality and effectiveness Vector Search, Full-text Search, Geospatial, Pattern match Data Science Knowledge Graph
  • 25. 25 1 Knowledge Graph Construction Gen AI use cases LLM Knowledge Graph
  • 26. Neo4j Inc. All rights reserved 2024 26 Knowledge Graph Construction with Cypher Templates
  • 27. Human 27 1 Knowledge Graph Construction Gen AI use cases LLM Knowledge Graph 2 RAG-based Chat Applications
  • 28. Neo4j Inc. All rights reserved 2024 28 Natural Language Search combining explicit and implicit relationships
  • 29. Application Human 29 1 Knowledge Graph Construction Gen AI use cases LLM Knowledge Graph 2 RAG-based Chat Applications 3 RAG-enhanced General Applications
  • 30. Neo4j Inc. All rights reserved 2024 30 Natural Language assistants and co- pilots, rooted in business policy Prompt + Relevant Information Embedding API LLM API User Database Search Prompt Response Relevant Results Knowledge Graph Application
  • 31. • Integrate Neo4j with leading LLM open-source frameworks such as LangChain and LlamaIndex • Call LLM APIs natively via Cypher using our open-source APOC library • Agnostic LLM orchestration connecting graphs to OpenAI, AWS Bedrock, GCP Vertex AI, Azure, Anthropic, Hugging Face, and other proprietary and open- source foundation models Integrate with the GenAI Ecosystem Neo4j Inc. All rights reserved 2024 31 GenAI Stack Application Generative AI & Embedding Models Orchestration Grounding Knowledge Graph Neo4jGraph Neo4jVector GraphCypherQAChain n Neo4jGraphStore Neo4jVectorStore KnowledgeGraphIndex Neo4j GenAI Integrations Text | Chat | Embedding NL Query | Image Gen Neo4j Drivers Java Python JavaScript
  • 32. • Co-Pilot in Neo4j Browser for autocomplete & Cypher generation • Bloom & NeoDash NL integration • More framework integrations: • Langchain, LlamaIndex, SemanticKernel, Spring.AI, Haystack POWERING GENERATIVE AI APPS Neo4j’s GenAI Roadmap Neo4j Inc. All rights reserved 2024 32 Coming 2024+
  • 33. • Parallel Runtime for faster analytical Queries • Change Data Capture better data integration • Autonomous clustering and Fabric for limitless scalability • Graph Schema, Improved Backup recovery, incremental import • Neo4j Ops Manager for managing databases • Aura Enterprise Database on all clouds (AWS, GCP, Azure) • SOC II Type 2 compliance, AuraDB APIs, RBAC configuration • Better observability with security log forwarding Performance metrics forwarding (EAP) • Private Link & CMEK (Coming soon) Neo4j product capabilities launched in 2023 Neo4j Inc. All rights reserved 2024 33 • Unified Developer Experience with Workspace • Self-service Data Import • GraphQL Support & Simplified Drivers API • Bloom support for GDS algorithms • GDS Python API • Knowledge Graph Embeddings • Longest Path & Topological Sort Algorithm • Vector Search • Real Time integration with Embedding APIs & LLM Models • Cloud Integrations (OpenAI + MS Azure OpenAI, VertexAI, AWS Bedrock, Langchain, LlamaIndex)
  • 34. Neo4j Inc. All rights reserved 20244 34