Lessons Learned Bot (LLB)
Description
In near real-time, the Lessons Learned Bot, or LLB, brings lessons learned (LL) documents to users through a Microsoft Excel add-in application locally installed to search for LL content relevant to the text within the selected Excel cell. The application will encompass a corpus of documents, a trained Machine Learning (ML) model, built-in ML tools to train user’s documents, and an easy-to-use user interface to allow for the streamlined discovery of LL content.
Detailed example
The LLB’s installation package comes with a pre-trained NASA LL dataset and a NASA Scientific and Technical Information (STI) dataset, as well as on-demand training tools allowing the user to apply the LLB search algorithm to their own discipline specific datasets. Additionally, we also have an API version of this software that can be called from any application within the Agency firewall.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Today, NASA’s LL are online and searchable via keywords. Nevertheless, users often face a challenge to find lessons relevant to their issues. Applying the advancement in Natural Language Processing (NLP) ML algorithm, the LLB can find and rank LL records relevant to text in the user’s selected Excel cells, containing just a few words or entire paragraphs of text. Results are displayed to the user in their existing Excel workflow.
Controls / human review
ATO: Not reported; PIA: Not published