KWS Saves Hours Daily with a Generative AI Enterprise Search Solution on AWS Cloud
For their daily work, R&D’s department of KWS needs to manage and extract relevant knowledge from a large number of unstructured documents. Given the considerable amount of information, this process is cumbersome and inefficient. KWS sought a solution to enhance and streamline information retrieval, providing quick and easy access.
access to company knowledge
automated data export from documents (from hours to minutes)
workloads required due to user-friendly interface
Background and Challenge Story
KWS faced a tremendous challenge in managing a vast number of documents and unstructured data, from scientific papers to patents. The task of extracting and locating relevant company knowledge in their systems was often inefficient and time-consuming, leading to a wasteful process.
The difficulty in accessing the necessary information, hindered the research and development department's ability to effectively gather the required company insights.
Consequently, they were on the lookout for a solution that could streamline the process, enabling them to easily and quickly retrieve the information they needed.
Solution Story
KWS has shown a strong enthusiasm for adopting Generative AI technologies for the purposes of text summarization, searching enterprise documents, and enhancing chatbot functionalities. They aim to strategically integrate these innovations in the Research & Development department, integrating more than 100,000 documents with Adastra's solution.Â
In response to our client's requirements, Adastra created a tailored enterprise search solution hosted on AWS, enabling research teams to perform searches based on context, utilizing the Amazon Bedrock Generative AI technology.
The solution was crafted for integration with MS Teams on a designated channel, enabling effortless communication for the end-users as if they were simply messaging a co-worker. Through this system, end users are able to input complicated queries and receive immediate, dependable answers from their "colleagues".
Impact
Generative AI large language models enable the research and development department to effortlessly gain access to the company knowledge that they need, saving significant time and providing a much more efficient process.
By tailoring the solution to be user-friendly, it allows the end users to smoothly communicate with the solution through MS Teams, allowing fast and reliable responses to complex queries and searches based on context.
- Significantly reduces the time required to extract company knowledge from documents.
- Represents an efficient process to manage context-based searches.
- Company knowledge and data were made easily accessible for the end-users.
- Enhanced user experience, end-user focused solution to reduce workloads.
- Leveraging AWS security features to keep data confidential.
About the ClientÂ
KWS is one of the world's leading plant breeding companies. Over 5,000 employees (excl. seasonal workforce) in more than 70 countries generated net sales of around $1,94 billion in the fiscal year 2022/2023. A company with a tradition of family ownership, KWS has operated independently for 165 years. It focuses on plant breeding and the production and sale of seed for corn, sugar beet, cereals, vegetables, oilseed rape and sunflower. KWS uses leading-edge plant breeding methods to continuously improve yield for farmers and plants' resistance to diseases, pests and abiotic stress. To that end, the company invested more than $320 million last fiscal year in research and development.
