HiveMind
HiveMind is a European Union (EU) project that accelerates software development and maintenance processes by using artificial intelligence and data technologies with a human-centered approach, continuously learning from user feedback, and providing reliable solutions with high contextual accuracy. As Tiga Healthcare Technologies, we lead the software development, maintenance and data-driven processes in the healthcare sector for this project.
- Co-funded by the European Union
Features and Benefits
This international initiative, bringing together 13 stakeholders from 9 countries through collaboration with leading research institutes, universities, and technology organizations, aims to accelerate and improve software development, maintenance and data-driven processes using artificial intelligence agents. The HiveMind project, for which Tiga Healthcare Technologies takes responsibility in the healthcare sector, creates a multi-agent framework that strengthens collaboration between developers and artificial intelligence agents by adopting a human-centered approach. This approach allows AI agents, customized based on organizational data, to optimize software processes. By automating intelligent system features, it minimizes errors and uncertainties.

- Multi-Agent Framework
- Intelligent System Specification
- Code Development and Test Automation
- Fine-Tuning with Corporate Data
- Dynamic Software Maintenance
- Agile Modeling and Continuous Feedback
- Data Security and Compliant Artificial Intelligence
- Cross-Industry Applications
- Open-Source Structure and Community Contributions
- Advanced Feedback and Learning Mechanisms
- Context-Aware Language Models and Customization
Multi-Agent Framework
HiveMind consists of artificial intelligence agents, each customized to support different roles within software development teams. These agents collaborate with human operators to accelerate and improve software development processes. Agents customized to meet the specific needs of companies ensure high efficiency at every stage of software projects.


Intelligent System Specification
The system's intelligent modeling and analysis mechanisms enable the automatic derivation of requirements and the resolution of inconsistencies. These mechanisms prevent errors at the beginning of the software development process and reduce the cost of later corrections. With agile modeling support, requirements are continuously improved.
Code Development and Test Automation
The system automates the coding, validation and testing processes. This automation feature accelerates the software development lifecycle, improving quality. The support for contract-based programming principles ensures the correctness and consistency of the written code.


Fine-Tuning with Corporate Data
The system enables fine-tuning with corporate data by providing companies with custom artificial intelligence agents. Through fine-tuning, more efficient, privacy-friendly and targeted results are revealed. The development of models tailored to the needs of organizations not only contributes to the optimization of processes but also helps gain a competitive advantage.
Dynamic Software Maintenance
The system continuously monitors and evaluates security vulnerabilities in software projects, providing automated repair suggestions. These suggestions facilitate software maintenance while ensuring the protection of security and performance standards. The dynamic monitoring infrastructure allows the software to adapt to current needs quickly.


Agile Modeling and Continuous Feedback
The system provides flexibility in software development processes through agile modeling techniques. AI agents, continuously learning from human feedback, quickly respond to project requirements at every stage of software projects. This approach enables faster development, testing and improvement of software projects. Thus, rapid prototypes are produced and user needs are addressed swiftly.
Data Security and Compliant Artificial Intelligence
HiveMind uses advanced encryption and data protection techniques to ensure the privacy and security of user data. The system provides reliable and ethical AI solutions in compliance with the European Commission's regulations on data and artificial intelligence. These solutions promote responsible practices in software engineering and offer a privacy-friendly structure that protects user data.


Cross-Industry Applications
The system enables the testing of software engineering solutions and their adaptation to a wide range of applications across various industries, including healthcare, automotive, manufacturing, and disaster response. AI agents understand the requirements of different sectors and offer customized modeling processes. This diversifies the application areas of software development approaches and fosters inter-industry collaboration.
Open-Source Structure and Community Contributions
HiveMind evolves continuously with community contributions as an open-source platform. The use of open-source Large Language Model (LLM) customization techniques allows developers and organizations worldwide to contribute to the platform and create more efficient solutions. This approach fosters the creation of an ecosystem that develops innovative solutions and contributes to software engineering.


Advanced Feedback and Learning Mechanisms
Artificial intelligence agents, continuously improving through Human-Machine Learning (HML) processes, become more precise and effective over time. These agents continuously learn through methods such as 'Human-in-the-Loop (HITL)' with human feedback integrated into the loop. As a result of this learning, the performance of these agents improves, leading to better outcomes.
Context-Aware Language Models and Customization
HiveMind enables the customization of large language models (LLM) based on organizational data. Language models developed using Retrieval-Augmented Generation (RAG) provide high contextual sensitivity in software development processes. This accelerates software processes and results in more consistent solutions.
