Learn how Google Cloud and Neo4j are addressing the pressing data challenges faced by organizations. In this session, we will delve into the significance of bringing data together and leveraging advanced AI tools to foster innovation. Despite the importance of data insights, a persistent data-to-value gap remains. Discover how the collaboration between Google Cloud and Neo4j bridges this gap and unlocks the true potential of your data. We will explore top use cases in various industry verticals, showcasing how these solutions drive meaningful outcomes. Additionally, gain insights into the seamless integrations Neo4j offers with Google BigQuery and Vertex AI, and learn how our co-solution approach tackles customer problems head-on.

1. © 2023 Neo4j, Inc. All rights reserved.
© 2023 Neo4j, Inc. All rights reserved.
1
B O S T O N

2. Proprietary + Confidential
Google Cloud and Neo4j
Solving Industry Challenges with Graph Data
Analytics and Generative AI
June 2023

3. Are we bringing
our data together
and applying the
latest AI and the
best tools to
innovate?

4. The ability to
access & act on
data insights is
vital. But a
data-to-value
gap still exists.
¹Source: HBR report, 2023
²Source: HBR report, 2023
76%
Yet only a third
Of leaders say the ability to access and analyze data
in real time plays a vital role in business performance.
Of leaders say they actually have mature, real-time
data access and analytics capabilities.

5. A unified, open and
intelligent data
ecosystem to
● Break down silos
● Improve efficiency
● Accelerate time to value
Predictions
Data
Relational
Databases
Data
Warehouse
& Data Lake
Machine Learning
& AI
BI
Non Relational
Databases
Applications
Visualizations
Analytics
Neo4j Graph DB (VM)
Aura DB (SaaS)
Neo4j Graph DS (VM)
Aura DS (SaaS)
Bloom

6. 900+ tech partners & growing
And a data cloud ecosystem that
is inclusive of our partners
Hundreds of tech partners integrations
Data Cloud Alliance
To solve enterprises’ modern data
challenges and accelerate the path to
value creation with data across all
industries

7. Proprietary + Confidential
Document Key-value In-memory Wide Column Graph Time-series Relational
DBaaS
Firestore
Serverless,
scalable document
store
Cloud
Bigtable
Low latency,
scalable wide
column store
MemoryStore
Managed Redis
Cloud
Bigtable
Low latency,
scalable wide
column store
Fastest Path to
Graph
Cloud
Bigtable
Low latency,
scalable wide
column store
Cloud SQL
Managed MySQL, PostgreSQL,
& SQL Server
Cloud Spanner
Scalable relational database
AlloyDB
Downloadable PostgreSQL
compatible database
Neo4j’s is Google Cloud’s strategic partner for graph databases

8. Proprietary + Confidential
Google: Your leading partner for AI success
Our pioneering research and development have made recent advances in AI possible.
Responsible AI at the foundation
History of Innovation

9. Proprietary + Confidential
Google Cloud: Expanding our AI portfolio
To support the needs of Generative AI-centric enterprise development
Business users
Developers
AI Practitioners
Vertex AI
Powered by Foundation Models
CCAI Document AI Discovery AI Healthcare AI
Conversation AI
Enterprise Search
Foundation
Models
Generative AI
App Builder
End-to-End ML Platform
Generative AI Studio | Generative AI APIs | Model Garden
Google Cloud Infrastructure - GPUs / TPUs
Powered by Foundation Models Powered by Foundation Models Powered by Foundation Models
Text
Dialogue
Code
Audio & Music
Image
Video

10. Healthcare &
Life Sciences
EMEA
JAPAC
AMERICAS
Global Google Cloud Customer Momentum
Retail CPG
Financial
Services
Telco
Media &
Entertainmen
t
Games
Manufacturin
g & Industrial
Supply Chain
& Logistics
Public Sector

11. Why Neo4j on Google Cloud?

12. Neo4j with Google Cloud is perfect fit
Sales alignment for co-solutioning to
meet customer needs
100% Google commit burndown for
partner solutions through Marketplace
Partner friendly cloud, 100% partner
attach for all customer deals
One team
AI/ML: Vertex AI, Gen AI Support
Analytics: BigQuery, Looker,
Dataflow, Dataproc
Application development: Google
Compute Engine, Google Kubernetes
Engine, Cloud Functions
Deep integrations Easy deployment
Easy click to deploy through Google
Cloud Marketplace, listed for SaaS or
VM deployments
Quicker time to value through deep
customer engagements such as on-
site hackathons, dedicated
workshops, and more
Pre-packaged vertical solutions e.g.
supply chain twin, fraud detection,
personalization & promotion, etc.

13. Neo4j Aura
Neo4j in Google Cloud ecosystem
Neo4j Connector for
Apache Kafka
BigQuery
Dataproc
Workbench
Vertex AI
Kafka
Cloud
Storage
Neo4j Connector for
Data Warehouse
Neo4j Connector for Apache Spark
Graph Data Science Graph Database Bloom

14. Vertex AI integrations, blogs, and workshops
Generative AI: Big announcements happening tomorrow!
Collaboration happening across five key areas
●A D2C company using Neo4j and BigQuery for Customer 360 for
personalized recommendations
●A global top 5 CPG Co. using Neo4j and BigQuery to optimize their
marketing budgets by increasing return on ad spend (ROAS)
●An Online retail platform using Neo4j and Vertex AI to better
combat retail fraud (real-time identification of potential threats)
●A CPG company is using Neo4j and Vertex AI for detecting
supply chain vulnerabilities, and making it resilient
BigQuery: Data Cloud & AI summit Keynote feature, Blogs, Demo
Google Cloud Ecosystem:
Neo4j is deeply integrated with Google Cloud products & ecosystem
AI / ML Analytics

15. Proprietary + Confidential
Supply Chain deep dive: Neo4j & Google Cloud - A powerful
combination for supply chain transformation
● Purpose-built supply chain twin solution
● Planet-scale Infrastructure as a Service. Fully managed
Multi Cloud Data Warehouse
● Industry-leading and flexible ML/AI toolchain
● Global market leader in graph technology
● Aligned with Google Cloud Supply Chain Twin
solution
● Compliments Google Cloud AI/ML and analytics
technologies
Deliver exceptional customer experiences Build a resilient & sustainable supply chain Run your supply chain autonomously

16. Proprietary + Confidential
Together, Google Cloud and Neo4j address many of today's most
challenging supply chain complexity issues
Demand Shaping Inventory Positioning Perfect Fulfillment Sustainability
Consider a omni-channel,
multi-echelon supply chain and
demand & supply risk to
determine optimized inventory
levels
Combine distributed order
management with warehouse
and transportation optimization
and enable automation of
processes
Reduce energy consumption
across operations, measure
risks, measure gas emissions,
adopt a circular economy and
measure the social impact of
your supply chain
Understand customers and
market trends to dynamically
adjust segmentation,
promotions and generate
highly accurate forecasts
Demand Shaping Inventory Positioning Perfect Fulfillment Sustainability

17. Proprietary + Confidential
Demo time: Neo4j + BigQuery -
Supply chain use case
Watch video: https://www.youtube.com/watch?v=Tu4INSYlmVs

18. Proprietary + Confidential
The Challenge
Global consumer goods company supply-chains were impacted
by disruptions in procuring/shipping of raw materials. They saw
10 times the number of disruptions in their supply chain from an
ingredient standpoint than ever before. Raw material shipments
were missing delivery deadlines which lead to production delays
and shelf-item shortages adversely affecting the company brand.
The company is building resiliency back in their supply chain to
help from a sales standpoint and improve stock levels. Improved
supply chain visibility will increase margins and reduce
disruptions which have been very costly
The Solution
Leveraging GCP and Neo4j for a resilient and “zero
disruption” supply chain
The company is working with Google Cloud to connect their
internal data sources with additional data sources which
power their supply chain decision making processes and
analytics.
The company is leveraging Neo4j to not only identify raw
material disruptions as they occur but more importantly to
predict disruptions updates on inventory, manufacturing and
more.
Neo4j and Google Cloud provide Graph Data Science and
predictable Supply Chain AI models to the company to
realize a “zero disruption” supply-chain
Global consumer goods company uses Google Cloud and Neo4j to
gain complete and constant visibility of their supply chain

19. ●Recommendation Engine
●Personalization &
Promotions
●Supply Chain
●Product catalog
●Advertising Optimization
●Fraud Detection
Neo4j & Google Cloud: Solving customer challenges, together
Financial services Retail & CPG Manufacturing & logistics Healthcare & Life Sciences
● Fraud Detection / Anti
Money Laundering
●Customer Journey / 360
●Identity and Access
Management
●Regulatory Compliance
●Knowledge Graph
● Digital Twin BOM
● Supply Chain Twin
●Connected Car
●Customer 360
● Patient journey and
outcomes
● Drug Discovery
● Supply Chain
●Genomics Research
●Knowledge Graph (R&D,
etc.)
Top use
cases
Select
customers

20. Proprietary + Confidential
● Want to discuss a problem that graphs can help with → Please reach out to your
Neo4j or Google Cloud Account Executive / POC
● Don’t know who your POC is? → Reach out to me jainrupal@google.com
What next?

21. Thank you

22. Appendix

25. Google Marketplace Link

26. Sales alignment for co-solutioning 100% partner attach
One team - Neo4j & Google Cloud
Google Cloud is a partner-led company, and that’s why you see
so many partners building billion dollar—or larger—practices on
our cloud.
“We're moving to a 100 percent partner attachment
strategy for all customer deals.”
- Thomas Kurian, CEO, Google Cloud
100% Google commit burndown through
Marketplace

27. ● Pre-packaged solutions with large scale applications, e.g.
supply chain twin, digital twin for BOM, retail focused
solutions, and more.
● Other use cases and solutions being developed
● Hackathons at customer site for focused problem solving to
significantly reduce solutioning cycle - e.g. a large retailer did
a week long hackathon to dive deeper into a specific
problem; and after successful solutioning is now deploying
the solution
● Neo4j / Vertex AI hands-on workshops: a 3 hour long
introductory workshop at Google Cloud offices or customer
site to train customer attendees (data scientists, analysts,
other personas) on graph + AI/ML use cases
Click to deploy through Google Cloud Marketplace, accessible through GCP console
Easy to deploy
Neo4j is easy to deploy on Google Cloud
Quick time to value
Vertical solutions

28. Proprietary + Confidential
The state of our world is impacting global supply chains in a myriad
of ways
Health
US disposable income
increased by $1.8 trillion in
2020, 81% from fiscal stimulus
Geopolitical
Sanctions on Russia have pushed
global commodity prices to their
highest in 50 years
Energy
The world’s demand for
electricity surged by 6% in
2021, adding to inflation
Climate
In 2019 a drought forced Taiwainese chip
plants to use water trucks, the equivalent
of 79,000 Olympic-sized swimming pools
Consumer
21% of the total global ecommerce
market is from online purchases,
creating a boom in shipping
Labor
There were more than 1 million truck
drivers in Japan in 2000, by 2030
that number is expected to halve

29. Proprietary + Confidential
Supply chains are more complex than ever before -
requiring a new approach
of supply chain companies have products
being held up in ports or across borders
68%
Fortune 1000 companies had a T1-2
supplier impacted by the pandemic
938
of supply chain companies are facing a
shortage of critical parts/ materials
74%

30. Proprietary + Confidential
Leading logistics company uses Google Cloud and Neo4j to gain
complete and constant visibility of their supply chain
The Challenge
This carrier’s mission is to create the most efficient
transportation network. Visibility is one of the major
challenges in the transportation industry. Having
complete and constant visibility is key to reducing cost,
time and providing efficient carbon friendly transportation
logistics network. Lack of visibility costs time and money.
The Solution:
Leveraging GCP and Neo4j for their supply chain visibility solution
Bottom line results include avoiding 4.3 million empty miles, avoided
3.5M MT CO2e emissions converting over-the-road loads to
intermodal, while improving driver safety records.
● Fleet equipment is IoT enabled streaming data in GCP
● Equipment is modelled with graph technology
● Graph data science and analytics are used to for predictive
analytics

31. Proprietary + Confidential
Use your real-time enterprise data to fuel your supply chain
twin, bridging data silos while maintaining the highest levels of
security
Enterprise Resource Planning Systems
(ERP)
Master data - Transaction data
Operational Technology Systems (OT)
IoT Devices - Gateways - Transportation Systems
Other Business Systems
Warehouse Management Systems
Transportation Management Systems
Digital Twin Private
Segment:
➔ Aggregated and
harmonized
enterprise data
➔ Secure in-transit
and at rest
➔ Highly available,
stored in region
for compliance
Your GCP BigQuery
Tenancy
3
2
1 4

32. Proprietary + Confidential
Business partners data ingestion
into your twin:
1. Ingest data from any cloud or on-prem
environments
1. Easy access to data already stored on
BigQuery
1. Stream data into BigQuery via APIs or via any
of our data streaming solutions
Easily and securely share your supply chain data with
business partners
Supplier data
Logistics provider
data
Customer data
Your GCP BigQuery
Tenancy w/ Partners
data views
Digital Twin
Community Segment:
➔ Share data with
business partners
securely and
seamlessly on a
‘collaboration room’
➔ Flexible data
ingestion to meet
your partners needs
Partner Collaboration
Room
3
2
1 4

33. Proprietary + Confidential
Complement your twin with real time public data sets to gain
a view of macro trends & events impacting your supply chain
Geo data
Weather (NOAA) - Traffic (public data sets) - Maps
(US Census Bureau) - Satellite (Google Earth
Engine) - Healthcare (public data sets)
Industry & markets news
Publicly available news (NYT) -
Data aggregators (Crux)
Sustainability data
Geospatial (Google Earth Engine, Climate Engine) -
Healthcare (public data sets) - Environment, Social,
Governance (World Bank, Factset), Greenhouse Gas
(Crux)
Digital Twin Public
Segment:
➔ Combine your
enterprise and
business partners
data with normalized
events/ trends data
for risk mapping and
scenario planning
Your GCP BigQuery
Tenancy
3
2
1 4

34. Proprietary + Confidential
Leverage Google Cloud AI/ML solvers for intra-day or what-if
supply chain simulations
Demand Shaping Inventory Positioning Perfect Fulfillment Sustainability
Understand the customers and
market trends to dynamically adjust
segmentation, individualize
promotions and generate highly
accurate forecasts
Use
Cases:
Customer
Segmentation
Price & Promotion
Planning
Demand
Forecasting
Consider a omni-channel, multi-
echelon supply chain and demand &
supply risk to determine optimized
inventory levels
Use
Cases:
Material Flow
Plannings
Procurement Doc
Analysis
Inventory Planning/
Optimization
Risk Management
Combine distributed order
management with warehouse and
transportation optimization and
enable automation of processes
Use
Cases:
Distributed Order
Planning
Assisted Order
Picking
Packing Visual
Inspection
Fleet Routing
Optimization
Multi Resource Ops
Planning
Contact Center AI
Reduce energy consumption in
manufacturing and warehouse
processes
Use
Cases:
Sustainability risk
forecasting
Greenhouse gas
emission
monitoring and
forecasting

35. Proprietary + Confidential
1
Reach Out To Your
Neo4j or Google Cloud
Representative
Get your questions answered by
our SMEs and plan for the next steps
that work for your organization
Host Joint Executive Briefing
Let’s review your use cases together
and explore how our solutions can
help you solve your biggest
challenges
2 3
Launch A Pilot
Conduct a pilot to assess solution
feasibility and performance in a real
environment
Get started today with Google Cloud & Neo4j
for your supply chain twin initiative