Periodic Reporting for period 2 - Giskard (Quality Assurance for AI)
Período documentado: 2024-07-01 hasta 2025-08-31
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.
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.
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.
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.
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.
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.