There is a rapid development in the field of Large Language Models (LLMs) which is reshaping the horizon of applied artificial intelligence allows not only isolated demonstration but also implementation of deployable systems that are capable of reasoning, extracting and reacting within a real-world environment. Still then there exist a persistent gap between the promising performance of fundamental models and the performance in production stage: problems like hallucination, limited context windows, stale knowledge and lacking of faultless interaction with other tools or dynamic data sources continue to undercut the trust and applicability. This book mainly addresses these gaps between the fundamental and practical application of LLMs in building the real-world systems capable of producing encouraging performance in association with other participating tools.

In the recent days there are two architectures have evolved that promising to bridge the above said gap: Retrieval Augmented Generation (RAG) and Multi-Agent based Systems (MAS). RAG is used to handle the knowledge and fundamental problem by interconnecting an external knowledge retrieval systems with internal generative technique, allowing the overall system to correct, updated, domain specific or proprietary information at execution time rather than only relying on parametric memory calculated at training time. Multi-agent architectures, in turn, address the reasoning and orchestration problem; decomposing complex tasks into specialized roles, enabling coordination among multiple LLM-driven agents, and allowing systems to plan, delegate, critique, and iterate in ways that a single monolithic model cannot achieve efficiently. Individually, each paradigm has generated substantial research interest and industrial adoption. Together, they form a powerful and increasingly necessary architectural foundation for the next generation of intelligent applications; yet the literature and practitioner resources addressing their integration, rather than their treatment as separate techniques, remain sparse.

The symposium particularly welcomes research addressing contemporary challenges through  artificial Intelligence, Machine Learning, Large Language Models, Retrieval-Augmented Generation (RAG), Multi-Agent Systems, Data Science, Cybersecurity, Cloud/Edge Computing, Software Engineering, and other emerging computing technologies. The uploaded proposal highlights the growing importance of integrating RAG and Multi-Agent Systems to develop reliable LLM-based systems capable of retrieving external knowledge, coordinating specialised agents, reasoning over complex tasks, and operating in real-world environments.

Original, unpublished work is invited on, but not limited to, the following areas.

• Retrieval-Augmented Generation: chunking strategies, hybrid semantic-lexical retrieval, re-ranking, multi-modal embeddings
• Multi-agent architectures: role design, coordination protocols, delegation, peer-critique and consensus
• Memory and state management: short-term, long-term, shared and private agent memory
• Evaluation methodology, benchmarks and metrics for RAG and agentic systems
• Hallucination mitigation, grounding and factuality
• Latency and cost trade-offs, scalability, and long-context management
• Safety, guardrails, prompt-injection defence, privacy, auditability and observability

• Enterprise and Software: automated customer support; autonomous software engineering and legacy code modernisation; enterprise knowledge management over multi-modal repositories
• Healthcare and Life Sciences: clinical decision support; clinical trial matching; scientific literature synthesis and hypothesis generation
• Finance, Law and Governance: real-time financial risk assessment; fraud mitigation in decentralised finance; legal contract analysis; legislative, ESG and policy compliance auditing
• Security: threat intelligence, incident response and grounded vulnerability patching
• Industry, Infrastructure and Environment: supply chain and logistics optimisation; structural health monitoring and smart cities; decentralised energy grid management; precision agriculture; air traffic and flight path optimisation
• Society, Media and Education: personalised and adaptive learning; investigative journalism and document mining; e-commerce personalisation; game design and narrative orchestration

Accepted and presented papers will be published in the Symposium proceedings, which will be submitted for indexing in some reputed database.

Registration details will be announced soon…