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Cover image for Editais.AI (http://Editais.AI) — AI-Matched Funding
Editais.AI (http://Editais.AI) — AI-Matched Funding Discovery for Public Sector Concept prototype: LLM-based matching engine that identifies federal funding opportunities for municipalities based on their strategic profile. A research prototype I built to explore AI-driven matching in complex regulatory domains. The idea: municipalities miss millions in federal funding every year because grant discovery is manual, fragmented across government portals, and requires reading hundreds of pages of technical requirements. The prototype Ingests active funding programs from multiple government platforms (federal and state-level) Builds a structured profile of each municipality (size, sector priorities, current projects, eligibility history) Uses an LLM to score fit between each grant and each municipality — not just keyword matching, but semantic alignment with strategic goals Generates a ranked list of opportunities with auto-drafted application outlines Why it matters This approach generalizes. Any domain where unstructured regulatory content meets structured eligibility criteria — grants, RFPs, tax incentives, compliance frameworks — can be approached the same way. The prototype validated the core architecture; the productization is ongoing through a sister project (DocLicit IA, which handles the downstream document generation step). Status Concept prototype and technical architecture. Used as the foundation for ongoing client conversations and as a reference implementation for similar matching problems in other verticals.
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