OUR DEMO CASES_
Smart software for mission-critical sectors
HIVEMIND integrates AI-driven agents into structured workflows, tackling complex software engineering tasks through intelligent command execution, adaptive batch processing, and automated input handling. Our framework ensures that every stage of development aligns with security, compliance, and efficiency standards, optimizing the entire SDLC in high-impact environments.
CITIZEN ENGAGEMENT_
Country
Romania
Lead Partner
Software Imagination & Vision SRL (SIMAVI)
The Objective
Enhancing smart city collaboration through AI-driven urban management.
The Challenge
SIMAVI develops digital platforms for community engagement but struggles with requirement collection, redundant processes, and maintaining alignment between system modules. Security and compliance with ISO/IEC 27000-series also add complexity.
The HIVEMIND Approach
- ElicitAgent ensures requirement completeness and traceability across development stages.
- QualityAgent maintains alignment between requirements and developed modules.
- CodeGenAgent automates redundant processes and provides development recommendations.
Expected Impact
DISASTER RESPONSE_
Country
Turkey
Lead Partner
HAVELSAN
The Objective
Streamlining emergency response through AI-driven coordination and automation.
The Challenge
HAVELSAN develops emergency response systems but faces challenges in system design, workload estimation, and maintaining coding standards. Fast-paced development cycles lead to inefficiencies in project coordination.
The HIVEMIND Approach
- ArchitectureAgent accelerates agile system modelling, improving documentation.
- TaskGenAgent enhances task estimation and workload distribution based on past data.
- CodeGenAgent ensures adherence to coding standards, reducing inconsistencies.
Expected Impact
HEALTHCARE_
Country
Turkey
Lead Partner
TIGA Healthcare Technologies
The Objective
Developing secure AI-powered software for auto-contouring organs in medical imaging.
The Challenge
TIGA specializes in AI-driven healthcare applications that must comply with strict data protection regulations. Ensuring software trustworthiness, secure-by-design principles, and compatibility with multi-architecture environments remains a key challenge.
The HIVEMIND Approach
- ElicitAgent ensures compliance with data privacy regulations from the early stages.
- QualityAgent maintains alignment between requirements and verification processes.
- DeploymentAgent optimizes containerized solutions for high-performance computing clusters.
Expected Impact
AUTOMATED MOBILITY_
Country
UK
Lead Partner
Queen's University Belfast (QUB)
The Objective
Ensuring reliability in perception and localization systems for autonomous vehicles.
The Challenge
Autonomous driving demands high-assurance software where safety, precision, and compliance are critical. QUB is developing an AI-powered prototype for autonomous driving, but ensuring software reliability, verification, and validation is a major bottleneck.
The HIVEMIND Approach
- CodeGenAgent generates structured, standards-compliant code for AI-driven perception and motion planning.
- QualityAgent & TestGenAgent automate validation & testing, detecting vulnerabilities early.
- MaintainAgent identifies and mitigates potential system failures, ensuring long-term reliability.
Expected Impact
MANUFACTURING_
Country
Germany
Lead Partner
Fraunhofer IWU
The Objective
Developing digital twins to enhance efficiency and energy optimization in manufacturing.
The Challenge
Fraunhofer IWU specializes in optimizing manufacturing processes through digital twins (DTs), but compatibility issues among diverse data sources cause delays in software development. Current implementations involve complex C/C++ and Python workflows, containerized with Docker in multi-architecture clusters.
The HIVEMIND Approach
- ElicitAgent & ArchitectureAgent define system requirements and resolve compatibility issues.
- CodeGenAgent generates code aligned with architecture, reducing misunderstandings between teams.
- DeploymentAgent optimizes CI/CD processes, managing Docker-based solutions in multi-architecture clusters.