Knowledge Graphs for
Critical Enterprise Systems
How knowledge graphs and GenAI combine in real-world solutions
Sreenath Gopalakrishna
Director of Software Engineering, BT
Dr. Jim Webber
Chief Scientist, Neo4j
1. Introduction to Knowledge
Graphs
2. Networks everywhere!
3. Evolution of SRIMS
4. Generative AI as a system
component
5. Competitive advantage
Agenda
Neo4j Inc. All rights reserved 2024
2
Knowledge Graphs are
cool.
Let me show you around
Neo4j Inc. All rights reserved 2024
3
It’s Not What You Know
Neo4j Inc. All rights reserved 2024
4
It’s Who You Know
Neo4j Inc. All rights reserved 2024
5
And where they are
Neo4j Inc. All rights reserved 2024
6
Higher Pay and More Promotions
• People Near Structural Holes
• Organizational Misfits
Network Structure
is Highly Predictive
Photo by Helena Lopes on Unsplash
“Organizational Misfits and the Origins of Brokerage in Intrafirm Networks” A. Kleinbaum
“Structural Holes and Good Ideas” R. Burt
7
Relationships
are the strongest
predictors of behavior
But You Can’t Analyse
What You Can’t See
Christakis & Fowler
Neo4j Inc. All rights reserved 2024
8
● Most data disciplines ignore
relationships
● It’s painful to manually engineer
connected features from tabular
data
● Graphs are built on relationships,
so…
● You don’t have to guess at the
associations
● With graphs, relationships are
built in
Node
Represents an entity in the
graph with optional label
Relationship
Connect nodes to each other
Property
Describes a node or
relationship: e.g. name, age,
weight etc
Graph Modeling is Straightforward
MICA
ANDRE
Name: “Andre”
Born: May 29, 1970
Twitter: “@andre29”
Name: “Mica”
Born: Dec 5, 1975
CAR
Brand “Volvo”
Model: “V70”
Since:
Jan 10, 2011 O
W
N
S
Neo4j Inc. All rights reserved 2024
9
BROTHER
SISTER
D
R
I
V
E
S
Index-Free Adjacency: Fast, Flexible, Scalable
Relational Database
Person Person-Friend Friend
Native Graph Database
At write time
Data is .connected.
as it is stored
At read time
.Lightning-fast. retrieval of data and
relationships via pointer chasing
Neo4j Inc. All rights reserved 2024
10
These simple
blocks are all
you need
Neo4j Inc. All rights reserved 2024
11
Nodes&
Labels&
Relationships&
Properties
Knowledge Graphs Help
BT Group Deliver Digital
Transformation
Sreenath Gopalakrishna, Director of Software
Engineering BT Group
BT Group OSS Division: We develop the
strategies and platforms that help
modernise BT Groups’s infrastructure,
driving convergence and automation.
13
BT Group |
The traditional network equipment deployment
approaches left a legacy of complexity and risk
• Multiple applications for each network technology
• Multiple vendors
• High maintenance costs
• Complex Application Integrations
Our challenge dimensions
14
Duplication
Closed
Platforms
Siloed
Data
Complexity
BT Group |
Our objectives were to create a platform that addressed
these fundamental capabilities:
The Proposed Solution - SRIMS
1. Self-Service framework for our network engineering
teams
1. Accessible digital twin platform
1. Real-time single source of truth
Benefits of a Graph
Database Approach
• Consolidation of siloed data
• Easy to extend and adapt
• Provides a single view of customers,
inventory and fault information
• Model physical and virtual environments
• Increased efficiency and performance
• Reduced Total Cost of Ownership
50,000
Product availability check
requests per day
It handles tens of thousands
of product availability checks
requests, each with strict
SLAs.
3,000
Users
With peak time concurrency
regularly passing 1500.
Significant savings per
day
Financial losses resulting
from the inability to transact
and process orders due to
product non-availability.
The business-critical nature of the project is reflected in the numbers:
What did we achieve?
5,000+
Order progress requests per
hour
SRIMS performs service
design and provisioning for
various products.
17
Measurable Gains: 65% reduction in OSS Apps, reduced time
to deploy new capabilities, modernised processes and
improved innovation culture.
BT Group |
Future Innovations
The future is positive for SRIMS both within BT Group and in
the wider Telco Industry.
BT Group are now supplying the SRIMS platform via a partner
to other Telecom Service Providers.
We are now exploring the use of Enterprise Knowledge
Graphs + LLMs in a RAG architecture to provide intelligent
searching of information to enable faster business decisions.
18
BT Group PowerPoint |
BT’s Asset
Knowledge Graph
Neo4j Inc. All rights reserved 2024
19
https://go.neo4j.com/rs/710-RRC-3
35/images/BT_SRIMS_Whitepaper.pdf
Are graphs for me?
Neo4j Inc. All rights reserved 2024
20
The Fastest Growing Database Category For 10 Years
Neo4j Inc. All rights reserved 2024
21
ISO SQL, meet ISO GQL
Neo4j Inc. All rights reserved 2024
22
The future is graph
The future is graph
Rethink what’s possible. Start building
Thank you for listening
Sreenath Gopalakrishna
Director of Software Engineering, BT
Dr. Jim Webber
Chief Scientist, Neo4j
Come talk to us at Neo4j Booth #324

BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf

  • 1.
    Knowledge Graphs for CriticalEnterprise Systems How knowledge graphs and GenAI combine in real-world solutions Sreenath Gopalakrishna Director of Software Engineering, BT Dr. Jim Webber Chief Scientist, Neo4j
  • 2.
    1. Introduction toKnowledge Graphs 2. Networks everywhere! 3. Evolution of SRIMS 4. Generative AI as a system component 5. Competitive advantage Agenda Neo4j Inc. All rights reserved 2024 2
  • 3.
    Knowledge Graphs are cool. Letme show you around Neo4j Inc. All rights reserved 2024 3
  • 4.
    It’s Not WhatYou Know Neo4j Inc. All rights reserved 2024 4
  • 5.
    It’s Who YouKnow Neo4j Inc. All rights reserved 2024 5
  • 6.
    And where theyare Neo4j Inc. All rights reserved 2024 6
  • 7.
    Higher Pay andMore Promotions • People Near Structural Holes • Organizational Misfits Network Structure is Highly Predictive Photo by Helena Lopes on Unsplash “Organizational Misfits and the Origins of Brokerage in Intrafirm Networks” A. Kleinbaum “Structural Holes and Good Ideas” R. Burt 7
  • 8.
    Relationships are the strongest predictorsof behavior But You Can’t Analyse What You Can’t See Christakis & Fowler Neo4j Inc. All rights reserved 2024 8 ● Most data disciplines ignore relationships ● It’s painful to manually engineer connected features from tabular data ● Graphs are built on relationships, so… ● You don’t have to guess at the associations ● With graphs, relationships are built in
  • 9.
    Node Represents an entityin the graph with optional label Relationship Connect nodes to each other Property Describes a node or relationship: e.g. name, age, weight etc Graph Modeling is Straightforward MICA ANDRE Name: “Andre” Born: May 29, 1970 Twitter: “@andre29” Name: “Mica” Born: Dec 5, 1975 CAR Brand “Volvo” Model: “V70” Since: Jan 10, 2011 O W N S Neo4j Inc. All rights reserved 2024 9 BROTHER SISTER D R I V E S
  • 10.
    Index-Free Adjacency: Fast,Flexible, Scalable Relational Database Person Person-Friend Friend Native Graph Database At write time Data is .connected. as it is stored At read time .Lightning-fast. retrieval of data and relationships via pointer chasing Neo4j Inc. All rights reserved 2024 10
  • 11.
    These simple blocks areall you need Neo4j Inc. All rights reserved 2024 11 Nodes& Labels& Relationships& Properties
  • 12.
    Knowledge Graphs Help BTGroup Deliver Digital Transformation Sreenath Gopalakrishna, Director of Software Engineering BT Group
  • 13.
    BT Group OSSDivision: We develop the strategies and platforms that help modernise BT Groups’s infrastructure, driving convergence and automation. 13 BT Group |
  • 14.
    The traditional networkequipment deployment approaches left a legacy of complexity and risk • Multiple applications for each network technology • Multiple vendors • High maintenance costs • Complex Application Integrations Our challenge dimensions 14 Duplication Closed Platforms Siloed Data Complexity BT Group |
  • 15.
    Our objectives wereto create a platform that addressed these fundamental capabilities: The Proposed Solution - SRIMS 1. Self-Service framework for our network engineering teams 1. Accessible digital twin platform 1. Real-time single source of truth
  • 16.
    Benefits of aGraph Database Approach • Consolidation of siloed data • Easy to extend and adapt • Provides a single view of customers, inventory and fault information • Model physical and virtual environments • Increased efficiency and performance • Reduced Total Cost of Ownership
  • 17.
    50,000 Product availability check requestsper day It handles tens of thousands of product availability checks requests, each with strict SLAs. 3,000 Users With peak time concurrency regularly passing 1500. Significant savings per day Financial losses resulting from the inability to transact and process orders due to product non-availability. The business-critical nature of the project is reflected in the numbers: What did we achieve? 5,000+ Order progress requests per hour SRIMS performs service design and provisioning for various products. 17 Measurable Gains: 65% reduction in OSS Apps, reduced time to deploy new capabilities, modernised processes and improved innovation culture. BT Group |
  • 18.
    Future Innovations The futureis positive for SRIMS both within BT Group and in the wider Telco Industry. BT Group are now supplying the SRIMS platform via a partner to other Telecom Service Providers. We are now exploring the use of Enterprise Knowledge Graphs + LLMs in a RAG architecture to provide intelligent searching of information to enable faster business decisions. 18 BT Group PowerPoint |
  • 19.
    BT’s Asset Knowledge Graph Neo4jInc. All rights reserved 2024 19 https://go.neo4j.com/rs/710-RRC-3 35/images/BT_SRIMS_Whitepaper.pdf
  • 20.
    Are graphs forme? Neo4j Inc. All rights reserved 2024 20
  • 21.
    The Fastest GrowingDatabase Category For 10 Years Neo4j Inc. All rights reserved 2024 21
  • 22.
    ISO SQL, meetISO GQL Neo4j Inc. All rights reserved 2024 22
  • 23.
  • 24.
    The future isgraph Rethink what’s possible. Start building
  • 25.
    Thank you forlistening Sreenath Gopalakrishna Director of Software Engineering, BT Dr. Jim Webber Chief Scientist, Neo4j Come talk to us at Neo4j Booth #324