BQ AI’s NSF-Funded Projects: Advanced AI Solutions for Data Access and Decision-Making

BrightQuery is proud to announce three NSF-funded projects in AI-driven data solutions, demonstrating our commitment to enhancing data accessibility and usability across various sectors. Each project addresses a unique facet of the data lifecycle, from data ingestion and processing to accessibility and AI-readiness, making BrightQuery’s platforms a central component in transforming complex data into practical, actionable insights.

Dr. Jose M. Plehn, Founder and CEO of BrightQuery, is the Principal Investigator for all three projects. With a Ph.D. in Economics, he has over a decade of experience leading transformative initiatives in AI-driven data solutions across diverse sectors. His expertise in developing hybrid AI models has positioned BrightQuery at the forefront of factual AI innovation.

These projects leverage our latest Factual AI™ innovations, including hybrid data fusion models, predictive analytics, and cross-functional AI interfaces, to create tools that align with BrightQuery’s mission to deliver high-impact, factual AI solutions across government, academic, and public policy sectors.

Project Details: Enhancing Data Accessibility through AI

Our three awarded projects represent targeted advancements in data processing and accessibility, tailored to meet specific needs across public and governmental sectors.

1. Data Access Alternatives, Artificial Intelligence-Supported Interfaces

  • Funding: $1.4 million (August 2024)
  • Lead Agency: National Center for Science and Engineering Statistics (NCSES)
  • Project Focus: Designed for researchers and educators, this project is centered on the development of AI-driven interfaces that make complex datasets more navigable and accessible. Utilizing advanced natural language processing (NLP) and machine learning models, we are building an interactive AI that interprets user queries, retrieves relevant statistical data, and presents it in a user-friendly format. The AI’s ability to cross-reference multiple data sources ensures Factual AI™ provides accurate, comprehensive results tailored to user needs.
  • Technical Details: This interface incorporates BrightQuery’s hybrid retrieval-augmented generation (RAG) model, which integrates both structured and unstructured data to deliver contextually relevant results. By dynamically generating responses from both structured datasets and external, relevant unstructured sources, the platform ensures accurate, comprehensive results tailored to user needs. Learn more at https://brightquery.ai/agentic/ 
  • Impact: This initiative will democratize access to scientific data, transforming complex educational and research datasets into accessible information. The AI’s ability to cross-reference multiple data sources will allow users to derive actionable insights with ease, enhancing academic research and public knowledge.

2. Building Capacity for State, Local, and Territorial Governments to Use Administrative Data for Evidence-Building

  • Funding: $1.26 million (August 2024)
  • Lead Agency: Bureau of Labor Statistics (BLS)
  • Project Focus: This project aims to empower government agencies with AI-driven tools for transforming administrative data into strategic policy insights. We’re developing a platform that not only ingests and processes large volumes of administrative data but also uses our Predictive Hybrid RAG Platform, a Factual AI™ solution, where government agencies can assess risks, predict trends, and drive data-informed policy.
  • Technical Details: Leveraging BrightQuery’s Predictive Hybrid RAG Platform, this solution integrates machine learning algorithms that analyze historical data and identify emerging trends, flagging anomalies that indicate shifts in socio-economic patterns. Using predictive modeling, the platform forecasts the impacts of potential policies, enabling government agencies to make proactive, data-driven decisions. Learn more at https://brightquery.ai/predictive/ 
  • Impact: By providing state and local governments with advanced analytics, BrightQuery’s tools will improve responsiveness to community needs, enhance policy development, and enable leaders to craft evidence-based solutions. This initiative will set a new standard for data-informed governance at the local level.

3. AI-Ready Data Products for Evidence-Building

  • Funding: $1 million (September 2024)
  • Lead Agency: Bureau of Economic Analysis (BEA)
  • Project Focus: This project is dedicated to developing AI-ingestible data products, paving the way for a National Secure Data Service (NSDS) that enables secure, cross-agency data sharing. By making statistical data AI-ready, BrightQuery’s platform will help streamline data access and enhance the analytical capabilities of federal agencies. This secure platform for AI-readiness reflects our commitment to Factual AI™ principles, ensuring privacy, integrity, and analytical depth.
  • Technical Details: The platform integrates BrightQuery’s Neuro-Symbolic Multi-Agent System, designed to ingest, standardize, and interpret large, complex datasets in a secure environment. The system uses a combination of neural networks and symbolic reasoning to align disparate data types, enabling seamless data linkage and compatibility with generative AI systems. This approach ensures privacy and data integrity, while still delivering the analytical depth required by federal agencies. Learn more at https://brightquery.ai/neuro-symbolic/ 
  • Impact: This foundational project lays the groundwork for a unified, AI-ready data infrastructure that serves as the backbone of federal data-sharing efforts. By creating a scalable, secure platform for AI-readiness, BrightQuery’s tools will enable the NSDS to maximize its potential for cross-agency collaboration and strategic decision-making.

BrightQuery’s Role in Data Evolution: Beyond Accessibility

Together, these projects reflect BrightQuery’s commitment to advancing AI capabilities in data processing, accessibility, and analysis. Each project tackles a critical data need—whether improving public access to educational datasets, enhancing government responsiveness, or preparing federal data infrastructures for AI applications. Our approach to factual AI ensures that these solutions are reliable, unbiased, and built to meet the highest standards of data accuracy and integrity.

By developing platforms that incorporate cutting-edge technologies such as hybrid RAG models, predictive analytics, and neuro-symbolic reasoning, BrightQuery is pushing the boundaries of what AI can achieve in the public sector. Our commitment extends beyond simply making data accessible; we’re creating tools that transform data into a strategic asset, empowering organizations at every level to make decisions that are as informed as they are impactful.

Looking Ahead: Building the Future of Factual AI

BrightQuery’s NSF-funded initiatives mark a significant milestone in our journey to redefine data’s role in decision-making. As we continue to develop and implement these projects, we’re laying the foundation for a future where data is universally accessible, securely shared, and analytically powerful. BrightQuery’s factual AI isn’t just changing how data is accessed—it’s reshaping how decisions are made, setting new standards for innovation across sectors.

Through our partnership with NSF and our ongoing commitment to technical excellence, BrightQuery is at the forefront of a data revolution. These projects are a glimpse into a future where AI empowers every decision, and where data is a foundational asset driving growth, insight, and transformation.