Reimagining Records Management: An Invitation to Virginia’s Cities, Counties, and Towns
As a career civil servant and (new) AI researcher, I am seeking pioneering State or Local government agencies in Virginia interested in revolutionizing their records management systems via artificial intelligence and natural language processing.
In the initial alpha testing phase, I aim to collaborate with an agency to transform its current records system into a cutting-edge, AI-powered information engine. This will be achieved by processing and indexing records with named entity detection (NED) and vector storage technology.
Learn More About Entity, Event, and Action (EEA) Based Records Management
For example, an entity could include the local public library.
Events could include a grant received,
or a renovation project.
The crux of this initiative lies in training an AI model on local government records produced by localities, boards, commissions, and agencies in Virginia. The aspiration is to build an Entity Detection and Linkage Model capable of identifying and understanding common government document types. Critically, the resulting vector database will comply with the Library of Virginia’s archiving policies, paving the way for vectorized storage to replace legacy file formats like siloed PDFs and Word documents.
Efforts of this magnitude understandably require significant time and financial investment. Should your agency have a budget allocated for this type of software project, your engagement would be of immense value. However, for agencies lacking the necessary funding, alternative sources, including grant funds, may be available to facilitate your involvement.
At its core, my project is about constructing a comprehensive, ledger-style record of internal and external government agency actions. While the immediate benefits involve enhanced usability of records and an automated method for archiving, analyzing, and converting unstructured documents into structured data, the long-term potential is immense. Eventually, agencies will integrate vector storage and structured records with other applications, significantly streamlining decision-making processes, boosting machine-to-machine efficiency, and improving transparency and accountability.
Want to get involved, but you don’t represent a government agency?
If this project sparks your interest and aligns with your vision for streamlined, AI-powered records management, I’d love to hear from you. I am currently assembling a team of AI engineers and professionals with experience in public sector administration to help design and test the first version of the model.
Join me in reshaping public sector records management and defining the future of government operations in Virginia and potentially beyond.