Image
Overview
The purpose of the service is to ensure that data protocols and pipelines are adequate to the AI application developed by the customer. The service can be delivered at different stages of product maturity to ensure that it can provide targeted testing when it is most useful. During earlier product development stages, the service concentrates on data collection, quality and storage protocols, whilst, at later stages, attention can be extended to scalability, access and control mechanisms.
More about the service
Discover more about our service, including how it can benefit you, the delivery process, and the options for customisation tailored to your specific needs!
The success of AI applications is almost without exception dependent on the quality of the data that is used during the training and testing phases. Nonetheless, ensuring data quality is often treated as a lesser detail. The same applies to data handling, the process by which data is collected, stored and accessed.
"Data pipeline evaluation for AI applications” addresses the above by providing a dedicated service to test the adequacy of the customer data pipelines or protocols for the AI product.
Before the service: A company has established data handling protocols that may be inadequate for optimal product development. The sources of data may be of limited quality. The collection and storage protocols may be poorly designed or implemented. Access to data may be cumbersome. Data may not be sufficiently secured. Redundancy protocols may be insufficient. All the above may result in an AI application that is of low quality, difficult to maintain or where data leakage may easily occur.
After the service: The company receives a detailed assessment and customised recommendations. For example, the customer can receive a thorough review of the adequacy of the current data handling setup, with potential weakness or identified bottlenecks. In addition, the customer can receive a set of recommendations for addressing shortcomings.
The service can provide the company with advice on both software and hardware solutions that can enable the AI solution to reach its full potential thus further enhancing the likelihood of operational success.
"Data pipeline evaluation for AI applications” addresses the above by providing a dedicated service to test the adequacy of the customer data pipelines or protocols for the AI product.
Before the service: A company has established data handling protocols that may be inadequate for optimal product development. The sources of data may be of limited quality. The collection and storage protocols may be poorly designed or implemented. Access to data may be cumbersome. Data may not be sufficiently secured. Redundancy protocols may be insufficient. All the above may result in an AI application that is of low quality, difficult to maintain or where data leakage may easily occur.
After the service: The company receives a detailed assessment and customised recommendations. For example, the customer can receive a thorough review of the adequacy of the current data handling setup, with potential weakness or identified bottlenecks. In addition, the customer can receive a set of recommendations for addressing shortcomings.
The service can provide the company with advice on both software and hardware solutions that can enable the AI solution to reach its full potential thus further enhancing the likelihood of operational success.
Logistics
The AgrifoodTEF project offers:
Data Pipeline Evaluation: Complete analysis of the customer’s present data solution, including stress testing under different scenarios.
Data Readiness Support: Assistance in preparing and managing existing datasets to ensure readiness for AI model training.Expert Guidance: Personnel available to support your experimentation and help you navigate the complexities of data handling.
Increased Exposure: Opportunities for the company to demonstrate enhanced models to industry stakeholders and customers.
Delivery Period: The service is available throughout the year, ensuring access support when required.Duration: Service execution can span several weeks and is dependent on the complexity of the task.
Location: The service is executed at RISE, Sweden, or remotely.
Customer Requirements:The company must provide access to relevant data or resources needed for the tests.The company’s personnel will be responsible for following all instructions provided by RISE.A PM detailing the test setup must be prepared and approved before starting the tests.
Deliverables:
Output: The company will receive a summary report detailing the tests conducted and the benefits of the service. Results will also be presented in a final review meeting.
The AgrifoodTEF project offers:
Data Pipeline Evaluation: Complete analysis of the customer’s present data solution, including stress testing under different scenarios.
Data Readiness Support: Assistance in preparing and managing existing datasets to ensure readiness for AI model training.Expert Guidance: Personnel available to support your experimentation and help you navigate the complexities of data handling.
Increased Exposure: Opportunities for the company to demonstrate enhanced models to industry stakeholders and customers.
Delivery Period: The service is available throughout the year, ensuring access support when required.Duration: Service execution can span several weeks and is dependent on the complexity of the task.
Location: The service is executed at RISE, Sweden, or remotely.
Customer Requirements:The company must provide access to relevant data or resources needed for the tests.The company’s personnel will be responsible for following all instructions provided by RISE.A PM detailing the test setup must be prepared and approved before starting the tests.
Deliverables:
Output: The company will receive a summary report detailing the tests conducted and the benefits of the service. Results will also be presented in a final review meeting.
The service can be adapted to specific customer needs.The assessment journey starts with a joint meeting where the customer discusses different alternatives with a technical team from AgrifoodTEF, supplemented with domain experts from RISE or Asta Zero and members from the customer support team.Once the service delivery plan is established, service delivery will begin.
Location
Remote
Sweden
Type of Sector
Arable farming
Food processing
Greenhouse
Horticulture
Livestock farming
Tree Crops
Viticulture
Type of service
AI model training
Collection of test data
Data analysis
Performance evaluation
Test execution
Test setup
Accepted type of products
Data
Software or AI model
