Summary
The adoption of AI technology is growing faster than ever, tripling from 2017 to 2021 (McKinsey). Risks of AI incidents, in particular with ethical biases, prediction errors, and cybersecurity, are rising. Current AI quality tools are insufficient and rely on manual testing, leaving a gap that AI/ML engineers cannot meet in terms of workload, costs & demand at the needed pace.
To address this need, GISKARD is developing an open-source and SaaS solution for companies that need quality assurance of their AI models. It provides a software platform for automated AI Quality Testing, Inspection & Remediation.
As a member of AFNOR, the French national standards council, GISKARD is committed to becoming the leading European software provider to help organisations prepare for the upcoming EU AI Act. EIC support is crucially needed to achieve this. In this project, GISKARD will optimise and validate its AI Testing solution and extend it to more use cases such as Time Series & Computer Vision.
To address this need, GISKARD is developing an open-source and SaaS solution for companies that need quality assurance of their AI models. It provides a software platform for automated AI Quality Testing, Inspection & Remediation.
As a member of AFNOR, the French national standards council, GISKARD is committed to becoming the leading European software provider to help organisations prepare for the upcoming EU AI Act. EIC support is crucially needed to achieve this. In this project, GISKARD will optimise and validate its AI Testing solution and extend it to more use cases such as Time Series & Computer Vision.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/190198093 |
| Start date: | 01-09-2023 |
| End date: | 31-08-2025 |
| Total budget - Public funding: | 3 704 441,25 Euro - 2 499 999,00 Euro |
Cordis data
Original description
The adoption of AI technology is growing faster than ever, tripling from 2017 to 2021 (McKinsey). Risks of AI incidents, in particular with ethical biases, prediction errors, and cybersecurity, are rising. Current AI quality tools are insufficient and rely on manual testing, leaving a gap that AI/ML engineers cannot meet in terms of workload, costs & demand at the needed pace.To address this need, GISKARD is developing an open-source and SaaS solution for companies that need quality assurance of their AI models. It provides a software platform for automated AI Quality Testing, Inspection & Remediation.
As a member of AFNOR, the French national standards council, GISKARD is committed to becoming the leading European software provider to help organisations prepare for the upcoming EU AI Act. EIC support is crucially needed to achieve this. In this project, GISKARD will optimise and validate its AI Testing solution and extend it to more use cases such as Time Series & Computer Vision.
Status
SIGNEDCall topic
HORIZON-EIC-2023-ACCELERATOROPEN-01Update Date
12-03-2024
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