Experiments by business librarians exploring how AI and official government data can close the business intelligence gap for early-stage entrepreneurs and small business owners, guided by librarian expertise, open principles, and responsible innovation at the frontier.
An experiment by two business librarians confronting the challenges of AI at the "jagged frontier" — building practical, responsible tools that combine official government data and librarian expertise to make credible business intelligence accessible to those who need it most.
Libraries are in a unique position within the business information landscape.
Libraries face many challenges in their mandate of supporting early stage entrepreneurs with business research. Regardless of size, budget or location, libraries are plagued by common constraints: business databases are very costly; their terms of use often restrict commercial purposes; and access is typically denied to relevant campus communities (e.g., alumni, local and regional community program participants that are served by campus innovation centers). Furthermore, many business research platforms are tailored to the workflows of finance professionals rather than entrepreneurs.
As a professional community, librarians have broad and deep knowledge of business information products, including their unique strengths and weaknesses across a variety of use cases. Librarians also have the technical and subject matter expertise needed to critically evaluate all aspects of user experience, such as usefulness, credibility and value. However, this knowledge is unevenly distributed and not organized in ways that could have more positive influence in the business information ecosystem.
Today the accessibility of relatively low cost of large-language-models (LLMs) and related computing services allows for the development of new, inexpensive ways to explore novel technical solutions for persistent business information problems. At the same time, the popularity of LLMs has presented many complex sociotechnological challenges, such as how to responsibly steward the development of uncharted technologies in order to allow productive and empowering use, rather than displacement or degradation of human capabilities. These challenges are dynamic, complex and have no clear answers. They require "experimentation and the capacity to allow a path forward".
The dataweb.ai initiative is an experiment by two business librarians to confront these challenges at the "jagged frontier". Through this initiative, we work on projects that lead to practical strategies for moving forward in uncertain times. This approach is guided by the following principles:
Rootwork is an AI-powered business research platform that leverages relevant official sources of government information and the expertise of librarians to produce credible information that is tailored to the needs of early-stage innovators and entrepreneurs taking their idea to market.
Rootwork is currently available by invitation only. You can request an invite from the sign-up link.
This project uses web-enabled AI to enrich SEC Form D filings — the primary public disclosure mechanism for exempt securities offerings.
By layering AI-assisted metadata enrichment and keyword extraction on top of existing Form D records, the project aims to build a richer picture of private capital fundraising activity. The goal is to develop a methodology for enriching public financial filings that helps entrepreneurs identify more relevant peers and fundraising opportunities.
Recent and upcoming talks
McKay, H., Perry, M., & Odem, S. W. (2026). Smart Growth on Lean Resources: Bootstrapping Library Entrepreneurship Support. Invited Panel. ALA Annual, June 25–29. Chicago, IL.
McKay, H. & Groenendyk, M. (2026). Dataweb.ai: How an AI-based research tool can help business librarians boost outreach activities and scale their impact. SOUCABL Conference, May 13–14. Owen Graduate School of Management, Vanderbilt University. Nashville, TN.
McKay, H., Torres, J., Archambault, S. G., & Crutchfield, T. (2026). How can AI support early business development? Spring workshop: "Where does AI fit? Optimizing business development with AI" — Entrepreneurship & Libraries Conference. Invited Panel. April 22. Online.
McKay, H. & Groenendyk, M. (Nov 20, 2025). dataweb.ai – Better Market Intelligence for Supporting Entrepreneurs. Entrepreneurship & Libraries Conference (ELC) 2025. November 19–20. Online.
Grants & Awards supporting this initiative
BRASS Research Grant Award (2026)
Presented by the Business Reference and Services Section (BRASS) of ALA,
this award recognizes dataweb.ai's innovative approach to addressing gaps
in how entrepreneurs identify comparable peer companies, exploring the use
of large language models and agentic systems to support more flexible and
efficient peer identification through metadata enrichment and keyword
extraction.
AWS Education Equity Initiative Grant
(2026–2027)
dataweb.ai received technical support through the AWS Education Equity
Initiative in making credible business intelligence more accessible to
underserved entrepreneurial communities.
Vanderbilt University Heard Libraries'
Digital Lab Seed Grant (2025)
dataweb.ai received a seed grant from the Heard Libraries' Digital Lab at
Vanderbilt University, supporting early-stage development of AI-powered
business research tools with a focus on responsible and practical
applications.
Press: Vanderbilt University News – "Heard Libraries' Digital Lab awards 2025 seed grants to trio of projects with AI focus." · RUSA Update – "2026 BRASS Research Grant Award."
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