Reliable and Accurate AI you Can Trust - Knowledge Graphs make [Gen]AI work

In a landscape where the expectations for Generative AI are rapidly evolving, this session will delve into the critical role Graph technology plays in advancing Retrieval-Augmented Generation (RAG). As recognized by Gartner and other leading analysts, Graphs are now pivotal in enhancing the accuracy and reliability of Generative AI. Attendees will learn how the integration of Graph technology with RAG [alternative: Semantic RAG / Graph Rag] not only addresses the inherent limitations of traditional models but also establishes a solid foundation for developing enterprise-grade Generative AI solutions that are precise, trustworthy, and capable of meeting the demands of today's data-driven world in highly regulated industries.

1. precision-engineered AI
TM
Saturday, August 31,
2024
PRESENTED TO
Reliable and Accurate AI
You can Trust.
Precision-engineered AI
Dr. Bernd Schopp Sebastian Gabler, MSc.
SquirroAG Semantic Web Company

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© 2024 SquirroAG, Semantic Web GmbH 2
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It is time for Enterprise Scalability
RETRIEVAL AUGMENTED GENERATION (RAG)

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Expectation: Transforming Business
with Intelligent Automation
Front-office employee efficiency will increase by 27% to 35% by 2026,
translating to up to $3.5 million in additional revenue per employee*
Economic Impact: Generative AI could
add $2.6 trillion to $4.4 trillion annually
across various industries, with retail
alone potentially benefiting by $400
billion to $660 billion through improved
marketing and customer service.*
*McKinsey & Company
Financial Services: Generative AI can
automate up to 70% of business activities,
leading to significant cost savings and
efficiency improvements.*
Manufacturing: Improved forecast accuracy by
27% and reduced scrap rates by 68% using
generative AI. AI implementation has improved
key performance indicators by 20-60%*
Pharmaceuticals: Generative AI has boosted
the performance of chemical compound
activity models by up to 2.5 times, reducing
lead identification times from months to
weeks*
Telecommunications: AI tools in this sector have
led to 28% improved service delivery and
reduced operational costs of up 12% , with
companies reporting meaningful revenue
increases and enhanced customer satisfaction*

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The Honeymoon is over –It is time to get serious

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Enhanced RAG –Trusted Generative AI
Agent Framework
Easily create and deploy
custom tools for complex
data processing pipelines,
leveraging large language
models (LLMs).
Knowledge Graph
Increase AI accuracy by using
knowledge graphs to reveal
hidden data hierarchies,
patterns, and relationships.
Data Pipelines
Seamlessly integrate
your structured datasets,
both first and third-
party, to build a
comprehensive
knowledge base for
LLMs.
AI Guardrails
Ensuring reliable, ethical,
and compliant decision-
making and
communication.
Ensure no personally identifiable
information (PII) is used.
-Accuracy
-Explainability
-Traceability

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Gartner: Knowledge Graphs make [Gen]AI work
"The range for knowledge graphs is Now
[…] as KG adoption has rapidly
acceleratedin conjunction with the
growing use of AI, generally, and large
language models (LLMs), specifically.
GenAI models are being used in
conjunction with KGs to deliver trusted
and verified facts to their outputs, as
well as provide rules to contain the model."

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© 2024 SquirroAG, Semantic Web GmbH 7
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Standard vs. Enhanced RAG
EXAMPLES

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Coffee Ordering –Standard RAG (Completeness)

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Coffee Ordering –Enhanced RAG (Completeness)

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Coffee Ordering –Standard RAG (Relations)
“What products contain milk, egg or soy?”

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Coffee Ordering –Enhanced RAG (Relations)

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© 2024 SquirroAG, Semantic Web GmbH 12
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7 Aspects for Graph Integration
ENHANCED RAG

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7 Aspects for KG Integration in a RAG architecture
Source: https://www.linkedin.com/pulse/seven-cases-knowledge-graph-integration-rag-andreas-blumauer-vjjbf
Shorten the
Time to Insight
Savvy querying
for the untrained
Lower costs for Implementation and
Maintenance
Overcome the Limits of Large
Language Models
User query assistant7
Provision of linked facts with the
help of knowledge graphs2
Personalization4
Provide additional context from
Knowledge Models1
Make use of
explainable reasoning
3
Fuse structured content with
knowledge models5
Efficient filtering of results6

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Discover enterprise knowledge with natural language queries
Question
Recommended
Content
Automatic
Summary
Graph Insights

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Learn more about Semantic RAG
https://www.poolparty.biz/semantic-retrieval-augmented-generation

16. precision-engineered AI
TM
Saturday, August 31,
2024
PRESENTED TO
Reliable and Accurate AI
You can Trust.
Precision-engineered AI
Dr. Bernd Schopp Sebastian Gabler, MSc.
SquirroAG Semantic Web Company