Quality Assurance for AI

Project Information

Giskard

Grant agreement ID: 190198093

DOI

10.3030/190198093

Project closed

EC signature date 22 August 2023

Start date 1 September 2023

End date 31 August 2025

Funded under

• The European Innovation Council (EIC)

Total cost

€ 3 729 395,43

EU contribution

€ 2 499 999,99

Coordinated by

GISKARD AI
France

Periodic Reporting for period 2 - Giskard (Quality Assurance for AI)

Reporting period: 2024-07-01 to 2025-08-31

Summary of the context and overall objectives of the project

The rapid adoption of AI technologies has precipitated a corresponding rise in concerns regarding ethical biases, prediction errors, and cybersecurity risks. Current AI quality tools predominantly rely on manual testing methods, creating a gap that strains the capacity and resources of AI/ML engineers amidst escalating demands.

In response to these challenges, Giskard is developing a comprehensive solution comprising both open-source and Software-as-a-Service (SaaS) platforms. These platforms are specifically designed to enhance the quality assurance processes for AI models across industries. Giskard’s initiative focuses on automating AI Quality and Security Testing, thereby empowering organizations to effectively manage and mitigate risks associated with AI deployments. This abstract outlines Giskard’s commitment to advancing AI quality assurance practices through innovative technological solutions, aimed at addressing critical challenges in AI deployment and ensuring the reliability and ethical integrity of AI systems in practical applications.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the EIC project, Giskard has successfully completed its Quality and Security testing platform for AI models for enterprise and open-source community. Beyond technical milestones, Giskard has also secured 2 patents and conducted extensive communication and dissemination activities to broaden its market presence.
Key accomplishments include:
Development of open source scan features to detect vulnerabilities and biases in AI models. These scans cover LLM, NLP, tabular, and computer vision models.
Development of an enterprise platform for scanning and testing Gen AI agents developed by large companies.
Development of a compliance platform to assess the conformity of the AI development against the EU AI Act.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The development of GISKARD's open-source and SaaS solution for AI quality assurance represents a significant advancement, addressing critical gaps in current manual testing. By automating AI Quality Testing, Inspection, and Remediation, GISKARD aims to enhance reliability and mitigate risks such as ethical biases and cybersecurity vulnerabilities.

Potential impacts include streamlining AI deployment across industries, fostering innovation, and building stakeholder trust. Key needs for further uptake and success include ongoing research and development to keep pace with technology, demonstrating effectiveness across diverse applications, accessing markets and finance for scalability, robust commercialization strategies, strong intellectual property rights protection, international expansion, and advocating for supportive regulatory frameworks.

Addressing these needs will maximize GISKARD's impact, accelerate market adoption, and establish it as a leader in ethical AI deployment worldwide.

Mitigate AI Risks with our holistic platform for AI Quality, Security and Compliance