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![... I think, the notion that [Saa]
business applications exist, that’s
probably where they’ll all collapse,
right in the Agent era..”
- Satya Nadella](https://image.slidesharecdn.com/masterdeckgraphsummitsydneypublic-250725012314-7e85f4f9/85/MASTERDECK-GRAPHSUMMIT-SYDNEY-Public-pdf-13-320.jpg)
![GenAI is changing how we develop
applications. Quickly.
"AI is fundamentally disrupting
software development ...”
-Innovation Endeavors (VC) / Axios, June 2025
“...AI pipelines need dynamic schemas
to [handle] evolving sources.”
-2025 Future Enterprise Resiliency & Spending, IDC
“A business data fabric reduces
latency and powers advanced AI…”
-Venture Beat, Enhancing business agility with rapid
data integration and advanced AI, 2025
"Organizations with rich, [connected]
knowledge graphs will have a
significant competitive advantage…”
-Gartner Perception is the New Superpower For the
Future of Analytics and BI, 2025
"[GenAI]…will disrupt the very
software that enabled the last wave
of transformation."
-Harvard Business Review, May 2025](https://image.slidesharecdn.com/masterdeckgraphsummitsydneypublic-250725012314-7e85f4f9/85/MASTERDECK-GRAPHSUMMIT-SYDNEY-Public-pdf-14-320.jpg)
![Schema: Unique relationship property,
relationship key, property data types
Property Based Access Control (PBAC)
for RBAC, data-driven rules to control
READ and TRAVERSE privileges on nodes
Ultra-high speed incremental importer
addition to offline importer
Incremental backup and recovery
Neo4j Ops Manager for improved visibility
Security &
Operations
Graph Schema Property Based Access Control (PBAC)
CORE DATABASE ENHANCEMENTS
GRANT privilege property
ON GRAPH {database|*}
FOR ( var:label )
WHERE condition
TO role
GRANT privilege element
ON GRAPH {database|*}
FOR ()-[ var:type ]-()
WHERE condition
TO role
Offline Incremental Importer Differential Backup & Point in Time Recovery](https://image.slidesharecdn.com/masterdeckgraphsummitsydneypublic-250725012314-7e85f4f9/85/MASTERDECK-GRAPHSUMMIT-SYDNEY-Public-pdf-76-320.jpg)
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- 5. Janelle Bailey, WA PoliceForce Jin Foo, Prospa Michele Howard, DXC “Weeks to seconds to investigate a link” “48 hours to 2 hours to approve a loan” “40% less employee attrition”
- 7. Agenda 09:40 Keynote: Graphs+ AI: Your Enterprise Advantage Neha Bajwa, Vice President Product Marketing, Neo4j 10:10 Unlock the Power of GenAI Tim Sheedy, VP Research and Chief AI Advisor, Ecosystm 10:30 AI as Archival Intelligence Dr. Keir Winesmith, Chief Digital Officer, National Film and Sound Archive of Australia 11:00 Morning Tea Break 11:30 How Prospa built a decision intelligence layer with Neo4j Jin Foo, Head of Data & Analytics, Neo4j 12:00 Neo4j: Product Vision and Roadmap Anurag Tandon, VP Product Management, User Tools and Developer Experience, Neo4j 12:30 Panel Q&A -All Guest Speakers
- 8. Agenda 13:15 Lunch andNetworking 14:15 Hands-On Workshops Workshop A: Create a Graph-Backed App from Scratch | Level 1 Darren Wood, Principal Solutions Engineer, Neo4j Emil Pastor, Head of Solutions Engineering ANZ, Neo4j Workshop B: Building Smarter GenAI Apps with Knowledge Graphs | Level 2 Ben Lumley, Senior Solutions Engineer, Neo4j Samko Yun, Senior Solutions Engineer, Neo4j 16:30 Cocktail and Networking Reception
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- 10. Slido & Survey Network: Eventsby Alpha Password: 238Castle Wi-Fi Let’s get you Connected
- 11. Fire Evacuation &Safety Briefing
- 12. Graphs and AI: YourEnterprise Advantage Neha Bajwa | VP Product Marketing
- 13. ... I think,the notion that [Saa] business applications exist, that’s probably where they’ll all collapse, right in the Agent era..” - Satya Nadella
- 14. GenAI is changinghow we develop applications. Quickly. "AI is fundamentally disrupting software development ...” -Innovation Endeavors (VC) / Axios, June 2025 “...AI pipelines need dynamic schemas to [handle] evolving sources.” -2025 Future Enterprise Resiliency & Spending, IDC “A business data fabric reduces latency and powers advanced AI…” -Venture Beat, Enhancing business agility with rapid data integration and advanced AI, 2025 "Organizations with rich, [connected] knowledge graphs will have a significant competitive advantage…” -Gartner Perception is the New Superpower For the Future of Analytics and BI, 2025 "[GenAI]…will disrupt the very software that enabled the last wave of transformation." -Harvard Business Review, May 2025
- 15. Application development starts with the rightquestions. Where When How Who What ?
- 16. Pre-GenAI Monolithic apps, rule-based automation 2023 2025 Silo’ddata Data layer; foundation for business logic The Evolution of App Development Database Interactive User Interface
- 17. Not-so-distant future The Evolutionof App Development 2023 2025 Today Personalized, dynamic, agent-driver systems Future AI Autonomy, real-time learning, self-adaptive business logic Interactive UI AI Model Agent Orchestration Database
- 18.
- 19. What if we storedrich context in an agile data layer?
- 20. Data, Meet Graph basedon Strengthen your Ready to
- 21.
- 22. Employees Network & Security Suppliers Product Customers Transactions Process 7Knowledge Graphs in an Enterprise
- 23. Customer Information History Payments Customers Uncover patterns inyour Recommendations Loyalty Programs Churn Prevention Customer Offers Dynamic Pricing Intelligent Ads
- 24. Extend to SevenData Types for Additional Use Case Applications Churn prevention + Interactions + Account + Interactions + Account + Location + Devices Customer 360 + Interactions + Account Segmentation + Account Loyalty Programs + Interactions + Account + Location + Devices Dynamic Pricing Recommendations Customer details Product Marketing Campaign Phone Identifier Email Address Country OrderLine Item LINE_ITEM FOR O R D E R E D PRODUCT P U R C H A S E D LOCATION INFORMS T A R G E T S ASSOC_EMAIL ASSOC_ID ASSOC_PHONE Order Customer Order Campaign Product
- 25. Customer Information Payments Recommendations Loyalty Programs Churn Prevention CustomerOffers Dynamic Pricing Intelligent Ads Uncover patterns in your History 80% Reduction in manual verification work 48hrs to 2hrs Reduction in loan approval time Customers
- 26. Uncover patterns inyour Assets Location Access Patterns Network & Security Identity & Access 360 Identity Resolution Reputation Scoring Threat Detection Zero Trust
- 27. Uncover patterns inyour Assets Location Access Patterns 4 min to determine blast radius Used to take hours or even days 100M Customers Protected Network & Security Identity & Access 360 Identity Resolution Reputation Scoring Threat Detection Zero Trust
- 28. Talent Learning &Development Career Management Orgs (who is who) Career Development Identity & Access 360 Identity Resolution Reputation Scoring Threat Detection Zero Trust Route Planning & Optimization Real-time Supply Chain Visibility Inventory Planning Risk Analysis Product Recommendations New Product Introductions Product Customizations Product Inventory Product Pricing Bottleneck Identification Process Improvement Process Automation Process Monitoring Recommendations Loyalty Programs Churn Prevention Customer Offers Dynamic Pricing Intelligent Ads Anti-money Laundering Digital Payment Scams Credit Risk Assessment Claims Fraud Credit Fraud Network & Security Suppliers Product Customers Transactions Process Connect your graphs to drive transformation Employees
- 29. Talent Learning &Development Career Management Orgs (who is who) Career Development Route Planning & Optimization Real-time Supply Chain Visibility Inventory Planning Risk Analysis Product Recommendations New Product Introductions Product Customizations Product Inventory Product Pricing Bottleneck Identification Process Improvement Process Automation Process Monitoring Anti-money Laundering Digital Payment Scams Credit Risk Assessment Claims Fraud Credit Fraud Employees Product Transactions Process Customers with graph transformation Identity & Access 360 Identity Resolution Reputation Scoring Threat Detection Zero Trust Network & Security Suppliers Recommendations Loyalty Programs Churn Prevention Customer Offers Dynamic Pricing Intelligent Ads Customers
- 30. Relationships connect nodes and representactions :LOCATED_IN Relationships can have properties (key:value pairs) :HAS_CEO start_date: 08-01 City Company Employee Relationships are directional Nodes represent objects Nodes can have properties The power of the graph model
- 31. Response Time Better Performance Number of Hops RelationalDB Graph DB Graph is fast
- 32. Easily add newdata without redesigning data model New data New data New data New data Graph is flexible
- 33. Graph is insightful Employees Network& Security Suppliers Product Customers Process Transactions
- 34. Up to Vertical scaling UnifiedDB for analytical & operational workloads Guaranteed Uptime SLA TB Graphs with Sharding Integrations with Any cloud. Any workload Encrypted Data SOC2 Type 2 HIPAA Compliant Graph Algorithms Graph is enterprise-grade and fully managed
- 35. 35 Trusted by 84of the 8 / 10 Top retailers 10 /10 Top automakers 10 / 10 Top US banks 9 / 10 Top aerospace & defence 9 / 10 Top telcos 10 / 10 Top technology & software 8 / 10 Top insurance companies 9 / 10 Top pharmaceuticals
- 37. Neo4j: Innovators leadingthe way Open source release 2007 Cypher Query Language launch 2011 First production-ready deployment 2009 Graph Data Science and MultiDB 2020 Neo4j AuraDB launch 2019 ISO announces GQL Standard 2024 Native vector search capabilities in Neo4j 2023 Browser and labels 2013 OpenCypher Project launched 2015 Distributed graph databases introduced 2017
- 38. Peer Approved, Recognizedby Analysts 2024 Gartner® Magic Quadrant™ Neo4j Named a Visionary in December 2024 Gartner© Magic Quadrant™ for Cloud Database Management Systems #1 Most Popular Graph Database with Developers Thanks to you all and 250k+ Developers across the globe
- 40. “Kiki brings togetherinformation across multiple disparate and siloed systems, improving the quality of that information and enabling our teams to ask anything—from resource needs to internal processes. It’s having a huge impact on productivity in ways that were not possible to imagine before without graph and Neo4j.” –Sebastian Siemiatkowski, CEO, Klarna 250,000+ Questions answered to-date 1,200+ SaaS platforms eliminated 85% Of Klarna employees use AI assistant Kiki Klarna Replaces 1,200 SaaS Apps with Graph-Powered AI Assistant Challenge Fragmented knowledge across 1,200+ SaaS apps created massive friction for employees. Solution Neo4j-powered knowledge graph integrated with OpenAI, delivered via ‘Kiki’ GenAI chatbot in Slack. Impact 85% employee adoption, 250K+ questions answered, massive gains in productivity and collaboration.
- 41. NEXT STEPS How canhelp you uncover hidden patterns and relationships with Graph?
- 43. JULY 2025 Taking GenAIto the Next Level VP RESEARCH Tim Sheedy
- 44. 44 ecosystm.io Organisations Are onDifferent AI Paths “Leading businesses build cross-functional AI teams, backed by senior leadership. Collaboration sharpens business cases and directs resources where they’re needed most – especially for skills." Source: Ecosystm , 2025 4% 34% 20% 19% 23% At the planning stage Experimenting/ Creating PoCs Testing pilots Scaled deployments within specific business lines Scaled deployments across the organisation "We’ve seen digital natives do in 24 hours what takes our industry six months." “Banks modernising their cores can leap ahead, powered by embedded AI."
- 45. 45 ecosystm.io Organisations Differ intheir AI Readiness Source: Ecosystm, 2025 0% 18% 5% 76% 1% Traditional Emerging Consolidating Transformative AI-First ORGANISATIONAL STRATEGY | DATA FOUNDATION | PEOPLE & SKILLS | GOVERNANCE FRAMEWORK
- 46. 46 ecosystm.io Drivers of GenAIAdoption Competitive Advantage 31% higher market differentiation. Operational Efficiency Average cost reduction of 24% in automated processes. Innovation Acceleration 41% faster product development cycles. Customer Experience 52% improvement in customer satisfaction scores. Early adopters show proven results
- 47. 47 ecosystm.io Impactful AI UseCases Operations 60% Intelligent Document Processing 57% Payment & Invoicing Automation 51% Real-time Inventory Management IT 61% Support & Helpdesk 55% Documentation 51% Code Generation & QC Other 55% Content Strategy & Creation 54% Recruiting HR CUSTOMER, SALES & MARKETING
- 48. 48 ecosystm.io Future Plans willsee Greater Adoption of AI OPERATIONS 70% Workflow Analysis 63% Fraud Detection & Prevention 61% Streamlining Risk & Compliance Processes CUSTOMER SUCCESS HR TECHNOLOGY 80% Cloud Resource Allocation & Optimisation 69% Automating Sales Processes 63% Location Based Marketing 61% Personalised Product/Service Recommendations 74% Workforce Planning 68% Talent Development & Training 62% Streamlining Employee Onboarding Source: Ecosystm, 2025 76% Network Optimisation & Performance Monitoring 70% Software Development & Testing
- 49. 49 ecosystm.io The Voice ofAsia Pacific’s Leaders "Our AI-driven recruitment screening for insurance agents streamlines the selection process, quickly identifying top candidates by analysing resumes and applications.” HR LEADER "With conversational AI, we can engage customers 24/7, answering their queries and resolving issues instantly, reducing the team’s workload and enhancing CX.” CX LEADER "AI is transforming how we work – from streamlining workflows to optimising transportation routes, making operations faster and smarter.” OPERATIONS LEADER "Using AI to streamline our sales pipeline has cut down the time it takes to qualify leads, enabling our team to focus on closing more deals with greater precision.” SALES LEADER "We’re finally unlocking our data! AI agents deliver personalised customer support at scale, and AI-driven network optimisation keeps our IT running seamlessly.” DATA SCIENCE LEADER
- 50. 50 ecosystm.io Operational Disruption • Systemintegrations break unexpectedly • Critical decision errors impact business • Productivity drops during remediation Risks of GenAI Missteps Reputational Damage • Public AI failures harm brand trust • Recovery takes 3-4x longer than building • 72% of consumers avoid brands after AI errors Financial Consequences • Failed AI projects cost $5M-$15M on average • Regulatory fines for non-compliance • Market valuation drops of 12-18% have already been experienced
- 51. 51 ecosystm.io Technology Barriers toGenAI Implementation Include: Cost Concerns High implementation and operational expenses Security Risks Data security and privacy vulnerabilities Regulatory Uncertainty Evolving legal frameworks across Asia Pacific Skills Shortage Limited AI expertise and training resources Data Challenges Poor data quality, accessibility and integration
- 52. 52 ecosystm.io The Data Challenge 52 ecosystm.io FragmentedData Landscape 86% struggle with siloed data across systems. 01 Insufficient Data Hygiene Poor data quality derails 72% of AI initiatives. 02 Contextual Limitations GenAI models often lack critical business context. 03 Linguistic Complexity Regional language diversity creates challenges. 04
- 53. 53 ecosystm.io Work is Requiredto Get Data “GenAI Ready” Organisational Data Readiness for GenAI (0-10) 4.9/10 COMPLIANCE 5.1/10 DATA SECURITY 5.1/10 DATA AVAILABILITY 5.5/10 DATA LINEAGE 6.8/10 DATA QUALITY “We actually have a semantic AI challenge: Our data has no understanding of relationships…”
- 54. GenAI LLMs overcome semanticAI challenges with billions of data points Graph Database helps you achieve the same outcome with your own organisation’s data
- 55. Our biggest GenAIchallenges are not technology: Inflexible business model and processes Lack of skills Employee fear
- 56. 56 ecosystm.io Next Steps forTech Leaders 1 Assess Readiness Evaluate current AI maturity and data quality gaps. 2 Invest in Talent Build AI skills through training and hiring. 3 Implement Semantic AI Leverage GraphDB for cohesive, contextual data use. 4 Ensure Governance Establish ethical frameworks and security controls. 56 ecosystm.io
- 57.
- 58. ● Identity resolution ●through graphs Jin Foo Head of Data & Analytics Prospa Identity resolution through graphs Jin Foo Head of Data & Analytics Prospa
- 59. ● Identity resolution ●through graphs Jin Foo Head of Data & Analytics Prospa Who is Prospa? Strong digital offering with low friction and fast speed to outcome Flexible funding solutions well suited to small business sector Sales and Service excellence Smart integrated cash flow solutions like Bill Pay and Xero Our offering
- 60. ● Identity resolution ●through graphs Jin Foo Head of Data & Analytics Prospa Our challenge – Empower ANZ SMEs Australia's small businesses significantly drive economic growth, contributing $600B to the economy and employing 5.4M people. However, these businesses face ongoing cash flow challenges.
- 61. Businesses may operatethrough intricate related entities Business Product Credit Bureau Contacts Accounts Type Terms Transactions Scores Default Owners
- 62. ● Identity resolution ●through graphs Jin Foo Head of Data & Analytics Prospa Graphs allow us to capture, visualise and query these complex relationships
- 63. ● Identity resolution ●through graphs We believe graphs simplify complex relationships Surfing Hidden Relationships: Multi-Entity Connections Fraud Detection Assessing Exposure Levels
- 64. Where to nextnow that Prospa is AI ready? 🚀 Stage 1: Retrieval-Augmented Generation (RAG) ”Let’s plug our knowledge graph into an LLM and ask questions.” 🤖 Stage 2: Agentic RAG “Let’s chain multiple RAG models into an end-to-end sales workflow.” 🧠 Stage 3: Model Context Protocol (MCP) “AI agents need to share state and have persistent memory.”
- 65.
- 67. Anurag Tandon Product Vision& Roadmap VP, Product, User Tools & Dev Experience anurag.tandon@neo4j.com
- 68. Your Business is aGraph Employees Network & Security Suppliers Product Customers Finance Process
- 69. Talent Learning &Development Career Management Skills Management Orgs (who is who) Job Search Account/Identity Control Reputation Scoring Threat Detection Access Control Zero Trust Route Planning & Optimization Real-time Shipment Tracking Inventory Planning Risk Analysis Product Recommendations New Product Introductions Product Customizations Product Inventory Product Pricing Bottleneck Identification Process Improvement Process Automation Process Monitoring Recommendations Loyalty Programs Churn Prevention Customer Offers Dynamic Pricing Intelligent Ads Anti-money Laundering Circular Payments Fraud Detection Employees Network & Security Suppliers Product Finance Process Your Business is a Graph Customers
- 70. Setting the Pace OpenSource Release 2007 Cypher Query Language Launch 2011 First Production-Ready Deployment 2009 Graph Data Science and MultiDB 2020 Neo4j AuraDB Launch 2019 ISO Announces GQL Standard 2024 Native Vector Search Capabilities in Neo4j 2023 Browser and Labels 2013 OpenCypher Project Launched 2015 Distributed Graph Databases Introduced 2017
- 71.
- 72. For developers, dataanalysts, and data scientists Premium, trusted cloud-native graph database, and analytics platform Cross cloud, easy to use, and enable AI accuracy
- 73. Fully Managed Seconds toSign Up Minutes to Wow Days to Value Integrated Ecosystem Strategic Investments Trusted Fundamentals Scalability with Enterprise Security, Governance, and Compliance c
- 74. Fully Managed Seconds toSign Up Minutes to Wow Days to Value Integrated Ecosystem Trusted Fundamentals Scalability with Enterprise Security, Governance, and Compliance Strategic Investments c
- 75. GQL as ISOStandard for Graph Queries Conditional Queries to provide more flexibility and expressive power to handle complex querying scenarios Quantified graph patterns & Quantified path patterns for simplified execution Cypher version can be selected at DBMS, database and single-query level: server upgrades do not require query migration. Query Language is decoupled from the server releases Language Enhancements MATCH (n:Person) CALL (n) { WHEN n.age > 60 THEN { SET n.ageGroup = 'Veteran' } WHEN n.age >= 35 AND n.age <= 59 THEN { SET n.ageGroup = 'Senior' } ELSE { SET n.ageGroup = 'Junior' } } RETURN n.name AS name, n.ageGroup Conditional Queries Graph Pattern Matching Quantified Path Patterns Cypher Versioning CORE DATABASE ENHANCEMENTS
- 76. Schema: Unique relationshipproperty, relationship key, property data types Property Based Access Control (PBAC) for RBAC, data-driven rules to control READ and TRAVERSE privileges on nodes Ultra-high speed incremental importer addition to offline importer Incremental backup and recovery Neo4j Ops Manager for improved visibility Security & Operations Graph Schema Property Based Access Control (PBAC) CORE DATABASE ENHANCEMENTS GRANT privilege property ON GRAPH {database|*} FOR ( var:label ) WHERE condition TO role GRANT privilege element ON GRAPH {database|*} FOR ()-[ var:type ]-() WHERE condition TO role Offline Incremental Importer Differential Backup & Point in Time Recovery
- 77. Block Format issuperior graph native format to group graph data into blocks that reduces amount of data read with greater performance in memory-constrained scenarios Parallel Runtime speeds up analytical queries up to 100x by concurrent execution on all cores CDC enables graph changes published as events in real-time (full or diff mode) Autonomous clustering with multi-db for multi-tenant SaaS solutions Performance & Scalability Block Format Parallel Runtime Change Data Capture Autonomous Clustering (with Multi DB) CORE DATABASE ENHANCEMENTS
- 78. Large Graph Support ● Highdata volumes-up to 100TB (and potentially more) of graph data ● Fast data loading-initial bulk import and staging/live incremental updates ● Semantic indexes-sharded full-text and vector indexes are natively integrated ● ACID-fully transactional and ACID compliant ● Simplicity-Transparent to user, standard Cypher ● Analytics-supports Neo4j tools (Query, Explore, Graph Analytics) ● Transparent to all API calls NEW CAPABILITIES EAP Available GA-Planned EO-Q3 2025
- 79. Strategic Investments Fully Managed GraphRAG TrustedFundamentals Scalability with Enterprise Security, Governance, and Compliance AI Accuracy Ease of Use 5Seconds to Sign Up Minutes to Wow Days to Value Integrated Ecosystem
- 80. Focus on YourApp, Not Infrastructure! Available on Google Cloud, AWS, and Azure 99.95% uptime SLA with self-healing cluster architecture Scale up to 512GB RAM for large memory-intensive graphs Automated backups and restore Automated upgrades, zero maintenance CLOUD FIRST CAPABILITIES More than 30k Managed Databases Available on all major cloud providers
- 81. Aura Launches 2024/2025 Feature: SecurityLog Forwarding GA Date: 2 July Feature: User Management Pro PLG- GA Date: 3 July Feature: 512GB RAM (AWS) GA Date: 8 July Feature: Customer Managed Keys (Azure) GA Date: 12 July Feature: Query Log Analyzer EAP Date: 22 July Feature: Customer Managed Keys (GCP) GA Date: 31 July Feature: Business Critical Tier v1 Date: 1st August Feature: 512GB RAM GCP GA Date: 13th August Feature: SSO Config (Admin UI) GA Date: 20 August Feature: Query Log Analyzer Date: 27 August Feature: Pro Trial Date: 2 September Feature: UPX-Preview Date: 2 September Feature: Change Data Capture Date: 4 September Feature: VDC Name Change Date: 4 September Feature: Query API GA Date: 6 September Feature: Migration Readiness Reports EAP Date: 6 September Feature: Console Consumption Reports GA Date: 16 September Feature: Mark DB as Production Date: 14 October Feature: Secondaries GA Date: 21 October Feature: Migration Readiness Report GA Date: 7 November Feature: 512Gi GCP Business Critical Date: 15 November Feature: Business Critical All Aura Regions Date: 19 November Feature: UPX GA Self Serve Date: 11 December Feature: 512GB Azure BC & VDC GA Date: 12 December Feature: Security Log Analyzer GA Date: 12 December Feature: Adaptive Email MFA GA Date: 15 December Feature: AuraDB Vector Optimised GA Date: 19 December Feature: India Region Pro & BC ‘all clouds’ Date: 7 Jan Feature: AuraDB Pro <128GB (pre-paid) Date: 13 Jan Feature: Aura CLI Date: 14 Jan Feature: GraphQL for AuraDB (BETA) Date: 14 Jan Feature: AuraDB Pro Trial 14 day length + all CSP Regions Date: 23 Jan Feature: AuraDB Latest version (CalVer) Date: 29 Jan Feature: AuraDB: Graph Analytics (Pro) Date: 13 Feb Feature: Custom Endpoints Date: 13 March Feature: VDC on UPX Default Date: 17th March Feature: Migration Tools & Guides GA Date: 26 March Feature: Direct import from cloud data warehouse (AuraDB Free, Pro & BC) Date: 26 March Q3 ‘24 Q2 ‘25 Q4 ‘24 Q1 ‘25 Feature: Online Tier Upgrades (Pro to BC) Date: 3 April Aura Graph Analytics GA (inc Sessions) Date: 7 May Feature: GraphQL API GA Date: 7 May Feature: Adjustable Storage (GCP, prepaid BC & VDC) Date: 8 May AuraDB Pro for Fabric Public Preview Date: 15 May Feature: HTTPS Connection for User Tools via console Date: 16 June Feature: Adjustable Storage (GCP, PAYG Po + BC) Date: 17 June Feature: Multi Factor Authentication (App Authenticator TOTPs) Date: 17 June Feature: Predefined roles (Professional) Date: 19th June
- 82. Comprehensive Cloud Offerings forYour Workloads Zonal (single AZ) with functionality aimed at smaller teams & departmental solutions Regional (Multi-AZ) with enterprise-grade SLA & functionality Highest tier, regional (Multi-AZ) with dedicated account provisioned per customer Perpetually free database for customers to learn and experiment with apps Now Available
- 83. 3 paid SKUs:Fit your workloads across Aura Professional, Business Critical, and Virtual Dedicated Cloud Free Trial: Try Aura Professional before you buy Scale Out: Secondaries provide ability to scale out for read heavy workloads Security: SSO using IDPs such as AAD and Okta, encryption in-transit and at-rest; CMEK, private VPC and private links, standard industry compliance New Capabilities Aura Pro (Free Trials) Secondaries For Scale Out AURA ENHANCEMENTS
- 84. Fully Managed GraphRAG Trusted FundamentalsScalability with Enterprise Security, Governance, and Compliance Cloud First AI Accuracy Seconds to Sign up Minutes to Wow Days to Value Zero Ops Integrated Ecosystem Strategic Investments
- 85. Unified Data Managementand Visualization Demo
- 86. Improved workflows witha single hub for all data management tasks Consistent user experience through a single unified console across Neo4j tools Easier collaboration as teams can share resources and collaborate on projects Improved productivity with GenAI copilot by helping developers write and improve Cypher queries Secure data access with expanded roles and new access controls Unified Experience Data Import (growing sources) One Click Graph Data Modeling AURA ENHANCEMENTS Co-pilot for Cypher Adoption AI Powered Dashboards
- 87. VS Code enablessyntax highlighting, auto completions, connection mgmt, and more JDBC Driver enables tool integrations, supports SQL translation, and schema mapping Neo4j GraphQL library and service to deploy low code API with GraphQL Query API (Cypher over HTTPS) allows for single Cypher requests with the response returned as JSON Model Context Protocol (MCP) Server Developer Surfaces VS Code Extension Drivers & Connectors DEVELOPER EXPERIENCE GraphQL Support Query API Coming Soon
- 88. Unified local consolewith Neo4j Enterprise Edition installation Convenience of offline working Enable remote connections, including to Aura Databases Unified login with Aura Migrate local databases to Aura Desktop V2 HYBRID DEVELOPER EXPERIENCE Coming Soon Coming Soon
- 89. Monitor & manageall Neo4j databases across the enterprise Identify security risks Use Aura tooling with self managed databases Easily migrate self managed databases to Aura with few clicks Fleet Management HYBRID ADMIN EXPERIENCE Aura (Unified Fleet Management) Aura Self Managed Coming Soon
- 90. Data Import & GraphData Modeling Integrated & Simplified Data Services Graph Analytics for All Enterprise Data
- 91. Pay-as-you-go, Serverless offeringproviding 65+ built-in graph algorithms for use with any enterprise data on any cloud platform New Graph Analytics Use Graph Analytics in any data in any system without full replication. Deliver most advanced graph algorithms in industry across CPU & GPU Deliver serverless experience so customers only pay for what they use Enable real-time execution with high throughput scenarios Enable interactive experiences with multiple analysts and data scientists running parallel algorithms GRAPH ANALYTICS AS KEY DIFFERENTIATOR Serverless Analytics Higher Scalability & Concurrency All Databases Projection Write Back
- 92. Graph Analytics (GDS)on Snowflake container service Use 65+ GDS algorithms to run in container service Simple SQL interface for data analysts and scientists Project data from Snowflake tables as a graph, run series of graph algorithms, write results back, shut down compute capacity INTEGRATED DATA ECOSYSTEM Snowflake
- 93. Auto provision AuraDBinstance Select OneLake Lakehouse + Tables Auto-generated graph schema using LLM Import using Fabric Spark Query and explore in Fabric directly INTEGRATED DATA ECOSYSTEM Microsoft Fabric
- 94. Strategic Investments Fully Managed TrustedFundamentals Scalability with Enterprise Security, Governance, and Compliance Cloud First Ease of Use 5Seconds to Sign Up Minutes to Wow Days to Value Zero Ops Integrated Ecosystem
- 95. Year of InnovationWith GenAI GenAI Integrations w/ Vertex AI June 2023 GenAI Stack with LangChain & Ollama Oct 2023 Vector Search & Store Added to Native Graph DB August 2023 GraphRAG Manifesto July 2024 Databricks Certification June 2024 Aura Console with Co-pilot Experiences Sept 2024 Aura Pro Trial with Vector support Aug 2024 Integration with Amazon Bedrock Nov 2023 Integration with Azure OpenAI Integration & Microsoft Fabric March 2024 New GraphRAG Capabilities for GenAI apps April 2024 GraphRAG Package Oct 2024 Vector Optimized Aura Instances Dec 2024
- 96. GenAI Language Statistics Creativity KGs Knowledge Facts Context Knowledge Graphs UnlockGenAI Accurate Contextual Explainable
- 97. What is GraphRAG? GraphRAGis RAG where the R path includes a knowledge graph.
- 98. The Benefits ofGraphRAG 1. Higher Accuracy 2. Easier Development 3. Explainability & Governance graphrag.com
- 99.
- 100. Vector Support RELEASED CAPABILITIES Vector Indexbuilt into the database Store any property, node, and relationship as vector in the database Ability to create embeddings by directly calling various embedding services like OpenAI, Azure OpenAI, VertexAI, and Bedrock Vector Type, Distance Function, Pre-Filtering, Scaling, external vector stores Coming Soon
- 101. Construct knowledge graphsfrom unstructured data/documents using schema Implement different GraphRAG retrievers Build GenAI RAG pipelines with vector and hybrid search and GraphRAG retrieval External vector search integration GraphRAG Python Package RELEASED CAPABILITIES
- 102. Integrated with GenAIecosystem Orchestration & Agent Libraries Support for major frameworks like Langchain, LlamaIndex, Spring AI, Langchain4j, Haystack, Semantic Kernel, etc. Integrated with all LLM platforms like AWS, GCP, Azure, and OpenAI Model Context Protocol (MCP), CrewAI, Pydantic.AI, other Agent SDKs GenAI Ecosystem RELEASED CAPABILITIES ● Graph Connector ● CypherQAChain ● KG Construction ● Vector Index Integration ● Multiple LangChain Templates ● LangChain.js ● LangChain4j ● Cypher Data Loader ● Vector Search Integration ● KG Construction ● Create Vector Index ● KG Construction ● Query Vector Index ● Embedding Retriever ● Dynamic Document Retrieve (Cypher) Coming Soon
- 103. AgenticRAG is anadvanced AI architecture that builds on traditional RAG by introducing autonomous agents to actively control and optimize the retrieval, reasoning, and generation process. Introduction to
- 104. Agentic Workflow User Asks Question Response GraphRAG Retriever LLM News Retriever EarningsCall Retriever Summary Retriever Next Steps Retriever Customer Competitor Articles Graph Earnings Call API Customer 360 Graph Companies Graph Orchestration Tools Grounding Sources
- 105. An agentic, API-drivenservice enabling developers to build GenAI applications in minutes ● Developer-Centric API provisioned at Database Level ● Dynamic Agent creation with configuration not code ● Simple UI to test chat experience and potentially embed in apps Agentic API in Aura NEW CAPABILITIES EAP-August 2025
- 106. Fully Managed Seconds toSign Up Minutes to Wow Days to Value Integrated Ecosystem Product Vision Summary Trusted Fundamentals Scalability with Enterprise Security, Governance, and Compliance c