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Events and Milestones

2024 - March

2024 - April

ONLINE @Ciklum Speaker’s Corner

A Live Coding Session


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AI is the new black, yet it takes skills and proper understanding to convert the buzzword into a working and scalable solution for real-life scenarios. Great news – a solution and main framework can be applied at any scale – from startups to enterprises. All you need is a great team.

Join our live coding session, where you will witness such a solution being created from the ground and adapted to a variety of environments by using different tech stacks 

Unlock practical knowledge within 2 hours. 

ONLINE @Ciklum 

Ciklum GenAI Upskill Program

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2024 - May

ONLINE @AI Doctoral Academy

Academic Lecture

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Course description

Building AI agents capable of lifelong learning represents an ultimate complexity task, closely tied to the breadth of context they can process. This course aims to explore cutting-edge techniques for constructing a full-stack, context-aware system from the ground up. It’s designed to be scalable, suitable for small applications as well as state and enterprise levels. We’ll discuss challenges related to scalability and the implications for data protection and privacy across various contexts, including personal data, financial nuances or military-grade sensitivity. Key concepts covered will include Conversational Agents Architecture, Retrieval-Augmented Generation (RAG) Architecture, streamlining unstructured data, Large Language Models, Knowledge Representation Techniques, Data Embedding, Retrieval, Semantic Search, and Reasoning.

Host Institutions


Course Duration

4 Hours (2 lectures, 2 hrs each)

Meetup in Bucharest

Google Developer Groups

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A RAG system essentially correlates a user’s prompt with a relevant data chunk. It does this by identifying the most semantically similar chunk from the database.

This chunk then becomes the context for the prompt. 

When passed to the LLM, it enables the system to provide a relevant answer within the given context.

In this workshop we will explore:

  • Processing highly complex, unstructured data.
  • Extracting meaning from data.
  • Practical knowledge representation techniques for handling large-scale context.
  • Real-time lexical and semantic search.

Conference in Bucharest


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AI chatbots are likely to be key in transforming our current approaches to UX and privacy. They can cover a broad spectrum of use cases, including impersonations, customer support, assistants, and even replacing parts of GUIs.

In this session, we will explore the challenges of coding a Multimodal AI Conversational Agent from the ground up, using RAG Architecture. The focus will be on scalability and managing unstructured data, providing a comprehensive overview of knowledge representation techniques, context understanding and reasoning, machine unlearning and privacy awareness.