DLA's global mission relies on a vast and diverse industrial base. Ensuring financial transparency and mitigating supply chain risk requires a comprehensive understanding of the economic relationships between DLA and its key suppliers. Current methods for this analysis are manual, time-consuming, and cannot effectively scale across thousands of vendors and millions of transactions. This SBIR topic seeks the development of an AI-powered tool to automate this process. The desired solution would integrate with DLA's business systems to identify significant vendor relationships and automatically retrieve publicly available financial data (e.g., from SEC filings). Using this data, the tool will apply a defined criterion for economic dependency (e.g., percentage of a vendor's revenue derived from DLA) to flag potential related parties. The solution should also be capable of assessing risk based on contract type (e.g., cost-reimbursement vs. fixed-price). The final tool must be designed to operate in a secure government environment and provide auditable, traceable results
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