AI-Powered Document Tagging System
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- Anywhere
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Project scope
- What is the main goal for this project?
-
BoardSpace aims to enhance its document management system by integrating an AI-powered feature that scans the content of uploaded documents to generate a list of suggested tags. This project involves developing a machine-learning model capable of understanding and extracting key themes and topics from various document types.
The goal is to streamline the tagging process, making it more efficient and accurate, thereby improving document retrieval and organization.
The project will require the team to apply their knowledge of natural language processing (NLP), machine learning algorithms, and software development to create a functional prototype. The learners will work on training the AI model, integrating it with the existing system, and testing its performance.
Key tasks include:
- Researching and selecting appropriate NLP and machine learning techniques.
- Developing and training the AI model using a dataset of tagged documents.
- Integrating the AI model with BoardSpace’s document management system.
- Testing and refining the system to ensure accuracy and efficiency.
- What tasks will learners need to complete to achieve the project goal?
-
The project deliverables will include a functional AI model integrated into BoardSpace’s document management system, capable of scanning and tagging documents accurately. Additionally, the team will provide a comprehensive report detailing the development process, the techniques used, and the performance metrics of the AI model. A user guide for the new feature will also be created to assist BoardSpace staff in utilizing the system effectively.
Specific deliverables:
- A trained and integrated AI model for document tagging.
- A detailed development and performance report.
- A user guide for the AI-powered tagging feature.
- What is the main goal for this project?
-
BoardSpace aims to enhance its document management system by integrating an AI-powered feature that scans the content of uploaded documents to generate a list of suggested tags. This project involves developing a machine-learning model capable of understanding and extracting key themes and topics from various document types.
The goal is to streamline the tagging process, making it more efficient and accurate, thereby improving document retrieval and organization.
The project will require the team to apply their knowledge of natural language processing (NLP), machine learning algorithms, and software development to create a functional prototype. The learners will work on training the AI model, integrating it with the existing system, and testing its performance.
Key tasks include:
- Researching and selecting appropriate NLP and machine learning techniques.
- Developing and training the AI model using a dataset of tagged documents.
- Integrating the AI model with BoardSpace’s document management system.
- Testing and refining the system to ensure accuracy and efficiency.
- What tasks will learners need to complete to achieve the project goal?
-
The project deliverables will include a functional AI model integrated into BoardSpace’s document management system, capable of scanning and tagging documents accurately. Additionally, the team will provide a comprehensive report detailing the development process, the techniques used, and the performance metrics of the AI model. A user guide for the new feature will also be created to assist BoardSpace staff in utilizing the system effectively.
Specific deliverables:
- A trained and integrated AI model for document tagging.
- A detailed development and performance report.
- A user guide for the AI-powered tagging feature.
About the company
- https://boardspace.co/
- 2 - 10 employees
- Technology, It & computing
BoardSpace is an online portal for the volunteer directors and administrators of condos, HOAs, non-profits and charities. BoardSpace overcomes the daunting task of looking after hundreds of documents, attending lots of meetings, preparing agendas, approving minutes and keeping on top of to-lists by providing boards with the tools to get their work done more efficiently and in less time.
Pat Crosscombe founded BoardSpace due to her experience on a condo board. BoardSpace is on a mission to organize the boards of directors of the world and was built by a team that understands the needs of condo and non-profit boards.
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