KCS
Proposal submitted to HORIZON-MSCA-2026-SE-01

KCS RESEARCH PROJECT

KGen4MICE

Lifecycle-aware knowledge and AI services for competitive MICE event operations

KGen4MICE is a research and innovation proposal for transforming fragmented event-management tools into a trustworthy, knowledge-driven AI ecosystem. It connects preparation, live execution and post-production so professional congress organisers can turn operational data into explainable decisions, adaptive services and cross-event learning.

Explore the project architecture

The challenge

Professional Congress Organisers operate under cost, seasonality, attendance, sustainability and global-competition pressures while submissions, scheduling, marketing, streaming and evaluation remain distributed across isolated tools. Knowledge is lost between event phases, limiting realistic planning, real-time adaptation and systematic learning.

Research questions

The questions connect the real-world problem with research activities and evaluable contributions.

  1. How can process-driven infrastructure preserve trustworthy knowledge across the complete MICE lifecycle?
  2. How can LLM-based information extraction convert weakly structured event content into reusable expertise assets?
  3. How can knowledge graphs support programme design, adaptive scheduling and scenario comparison?
  4. How should agentic EventOps assistance personalise outreach and participant engagement while remaining governed?
  5. How can real-time visual intelligence combine streaming, translation, prediction and dashboards for operational decisions?

The research-project architecture

The KGen4MICE architecture connects the event lifecycle with shared capabilities for trustworthy services, information extraction, knowledge graphs, agentic support and visual operations.

Figure: Compact KGen4MICE conceptual architecture. Five shared intelligence capabilities support preparation, execution and post-production as one continuous event lifecycle.

The architecture is read in two directions. Horizontally, an event moves from preparation through live execution to post-production, with knowledge from the completed event improving the next planning cycle. Vertically, five reusable capabilities support every phase. WP1 provides the trustworthy process, cloud, provenance, digital-twin and governance foundation. WP2 extracts structured information and expertise from weakly structured event content. WP3 turns that information into knowledge-graph-driven programme and scenario intelligence. WP4 uses the governed knowledge to support personalised engagement and operational assistance. WP5 exposes real-time visual, streaming, translation, predictive and dashboard capabilities to organisers and participants. The result is not five isolated tools, but one lifecycle-aware service-intelligence system.

INTERNATIONAL CONSORTIUM

Philippe Tamla’s involvement in KGen4MICE

Prof. Philippe Tamla is involved in the international consortium that prepared and submitted the KGen4MICE research proposal to the HORIZON-MSCA-2026-SE-01 call. The collaboration brings together the research, technical and sector perspectives required to connect service processes, information extraction, knowledge graphs, agentic AI and visual event operations across organisational and national boundaries.

His involvement reflects experience in shaping interdisciplinary research through connected work packages, coherent system architecture and transferable innovation objectives. KGen4MICE is presented as a submitted proposal; funding and future results are not implied.

Research workstreams

Each workstream addresses a distinct part of the project while remaining connected to the shared architecture and questions.

WP1 — Trustworthy infrastructure

Process-driven service infrastructure, formal requirements, ontology governance, provenance, secure cloud services, persistence, digital twins and audit logging.

WP2 — Information extraction

LLM-based extraction of expert information, assignments, transcripts, multilingual sentiment, profiles, recommendations, entities and topics.

WP3 — Knowledge-graph intelligence

Lifecycle-aware event and expertise knowledge supporting programme optimisation, evidence, scenarios, locations, engagement and adaptive scheduling.

WP4 — Agentic EventOps

A governed copilot for personalised outreach, conversational engagement, marketing automation, real-time interaction and strategic learning.

WP5 — Visual operations

Digital signage, hybrid streaming, real-time translation, predictive analytics, operational monitoring and interactive dashboards.

Project highlights

  • The proposal defines AI for Services 2.0 as a continuous knowledge-driven service-intelligence model across event preparation, execution and post-production.
  • Five interconnected scientific breakthroughs connect trustworthy infrastructure, LLM-based information extraction, knowledge graphs, agentic intelligence and visual operations.
  • Prof. Philippe Tamla is involved in the international consortium that submitted KGen4MICE to the HORIZON-MSCA-2026-SE-01 call. KGen4MICE is currently presented as a submitted proposal.

Research and supervision

KCS supports students, researchers and supervisors in connecting a relevant problem with appropriate methods, careful evaluation and a clear written or technical result.

Ways to participate or collaborate

  • Workshops on lifecycle-aware AI and knowledge architectures for complex service organisations.
  • Research collaboration on information extraction, knowledge graphs, agentic systems and visual analytics.
  • Design reviews for trustworthy AI, provenance, digital twins and process-driven cloud infrastructure.
  • Coaching for interdisciplinary researchers connecting scientific breakthroughs, work packages and demonstrable service outcomes.

ENGAGE WITH KCS

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Tell KCS whether you want to learn the method, join or propose a project, supervise researchers, evaluate a related idea, or develop a comparable research and innovation programme.

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CONTACT / APPOINTMENTS

Contact / Termine

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Email: contact@kcslab.orgWhatsApp: +49 176 72199023

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