Hybrid intelligence startup cooperation with governments and companies in the US and Europe?

With the rise of AI and the demand for digital transformation, both public and private actors increasingly want to use intelligent decision systems in the data-driven world.

However, due to trustworthiness concerns and accuracy and precision challenges, users and clients hesitate to adopt such systems.

To address these issues, Smart Navigator focuses on developing a novel system architecture that integrates human and machine components to generate a unique hybrid intelligence approach.

In parallel, the project improves a previously developed model for prediction and simulation with higher accuracy.

As key deliverables, a novel architecture for hybrid intelligence in decision technology was developed, an innovative Multi-Space Analysis Model for complex network analysis was configured, and related policy briefs and papers were published.

This work targets non-technical executives and mid-senior staff in strategic sectors, as well as public sector teams.

The expedition outcomes provide a valuable knowledge base for researchers, practitioners, and AI experts. Using hybrid intelligence to address public and private sector AI challenges can support ethical, responsible, and human-centric decision systems.

We gained deep insight especially in hybridizing rule and pattern-based methods with knowledge graph approaches for event and object recognition, relation extraction, and integration with data collection, processing pipelines, and dynamic ontology structures.

With this hybridization, it becomes easier to achieve high accuracy rates for detection and relation extraction in complex and dynamic environments.

Very fruitful collaborative conditions were established between the US Node and the explorer. A. Ridwan Hossain (PhD Researcher, NJIT) noted that Smart Navigator has great potential to address future AI decision technology challenges. Arif Hossain (PhD Researcher, NJIT) highlighted its innovative features and high accuracy in complex event and object recognition.

We sincerely appreciate the NGI Explorer program for providing a highly productive collaboration environment that accelerated this exploration.