From vision to real value | Generative AI (GenAI)

Discover the potential of GenAI and learn how it can enhance your organization’s operations. In our presentation, you’ll find real case studies showcasing how artificial intelligence is revolutionizing our clients' businesses. See how automation, data analysis, and intelligent tools support company growth across various industries. Explore the tangible benefits of implementing GenAI – from boosting operational efficiency to innovative customer service approaches. Find out how you can leverage these opportunities in your organization!

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1. From Vision to Real Value:
How and Where to Leverage GenAI?

2. Artificial Intelligence (AI) - Technology designed to create systems that mimic
human actions, such as language understanding, decision-making, problem-solving,
and simulating human intelligence in reasoning, learning, and adaptation.
Machine Learning (ML) - A technique enabling AI systems to learn from data
independently, building predictive models instead of relying on explicit
programming. For example, detecting financial fraud based on transaction patterns.
Key concepts and definitions

3. Deep learning (DL) - An advanced form of machine learning using multi-layer neural
networks inspired by the human brain. It excels at analyzing complex, unstructured
data like images, audio, or text, enabling AI to recognize images or transcribe speech.
Generative AI (GenAI) - Built on Deep Learning, it not only analyzes data but also
creates new content like text, images, music, or code. This innovative AI field
is widely used across industries.
Key concepts and definitions

4. Automation - A distinct concept often mistaken for AI. Unlike AI, it performs
repetitive tasks based on predefined rules, executing processes without the ability
to improve independently.
Large Language Model (LLM) - A language model using billions of parameters
to generate responses, enabling deep understanding of context and linguistic
nuances, e.g., ChatGPT.
Key concepts and definitions

5. Key concepts and definitions
Foundation Model - A versatile base model trained on large datasets, adaptable
for various applications, e.g., Claude, Llama, or Stable Diffusion.
Fine-tuning - Adjusting an AI model with specific data to meet particular industry
or problem needs.
Retrieval-Augmented Generation (RAG) - Combines information retrieval
with content generation for accurate, relevant AI responses.

6. AWS Cloud Adoption Framework for Artificial Intelligence

Source: AWS Whitepaper, AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI
Current regulations and policies related to GenAI

7. AI usage policies - a guide for Businesses:
▪Define goals and scope
▪Establish testing and monitoring procedures
▪Plan risk management and regulatory compliance
▪Provide training and engage employees
▪Ensure ethical AI use
▪Manage data and ensure GDPR compliance

Current regulations and policies related to GenAI

8. Why develop an AI policy?
▪Building trust
▪Ensuring regulatory compliance
▪Managing risks
Other regulations to know: Digital Markets Act, Digital Services Act
and Industry-specific Regulations for AI Implementation
Summary of Key Points
EU AI Act
AI Usage Policy
Data management
Employee training
Current regulations and policies related to GenAI

9. Customer:
▪A low-code platform for remote collaboration and task management, offering
features like task assignment, project tracking, calendar management and document
sharing for business users across industries.

Challenges:
▪The onboarding process was too lengthy, taking up to 3 months, with high costs due
to mentors' involvement. Communication barriers and lack of motivation hindered
efficient onboarding, with new hires preferring to ask a bot over mentors.
Case Study 1: Chatbot for onboarding support

10. Solutions:
▪An AI chatbot integrated Amazon Q for Business with Slack, company PDFs, video tutorials
and a knowledge base. The bot acted as a personal onboarding assistant, providing instant
answers and combining information from Slack, PDFs and videos.
Benefits:
▪Productivity and motivation increased, as communication barriers were reduced, enabling freer
interactions with the chatbot. Onboarding time shortened with immediate answers, reducing
costs by 40%, and the solution proved scalable for other areas, like customer support.

Learn more by reading the full case study.
Case Study 1: Chatbot for onboarding support

11. A food production company in the FMCG sector aimed to automate quality control
to address high costs, human error, and subjective evaluations.

An AI-powered system processed images from 4 cameras on 4 production lines,
assessed packaging quality, and removed defective products automatically.
The solution reduced labor costs, minimized errors, and optimized defect detection using
YOLO models, ensuring scalable and efficient quality control.

Want to learn more? Download the full case study by clicking this link.
Case study 2: Image analysis on the production line

12. A platform for personalized diets and recipes utilized AI to enhance user experience and
support rapid growth.
The AI-powered virtual nutritionist provided personalized recommendations,
faster responses and natural communication, ensuring data security via AWS.
Key outcomes included faster order completion, cost savings, improved
user satisfaction and scalable, secure operations.
Learn more by exploring the full case study.
Case Study 3: Virtual Nutritionist

13. Funding Options and POC for GenAI Projects

Proof of Concept with LCloud
▪Collaboration with experienced engineers specializing in AI projects,
▪Support in selecting the right technology, working with data, and managing the entire
AI adoption process in your company,
▪Access to AWS funding programs, requiring only your team’s involvement
as an investment,
▪Opportunity to receive up to $10,000 in non-repayable funding.

14. LCloud and AWS support you in EU funding programs by:
▪assessing opportunities to secure EU funding,
▪identifying relevant grant competitions,
▪planning and optimizing architecture,
▪collaborating with firms specializing in grant applications,
▪meeting environmental requirements,
▪selecting subcontractors for R&D, including academic partners,
▪participating in international projects.
Funding Options and POC for GenAI Projects

15. Contact us
LCloud Sp. z o.o.
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00-120 Warszawa
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