Treasury Agent

The Problem Federal grants are a massive source of non-dilutive capital, yet the path to securing them is paved with bureaucratic friction. Most existing AI solutions in this space are "chat wrappers"—static interfaces that generate text but lack operational output, stateful memory, or the ability to navigate live government infrastructure. The Solution fervoAI Treasury Agent is not a chatbot; it is autonomous infrastructure. It operates in a continuous stateful orchestration loop to bridge the gap between innovation and capital. Built for the Milan AI Week Hackathon, the agent identifies targets, calculates feasibility in real-time, and deploys specialized swarm workflows to close the execution gap. Key Technical Features Semantic Target Acquisition: Real-time query expansion against live Grants.gov S2S (System-to-System) API surfaces. Feasibility Matrix: Dynamic relevance ranking using Gemini 2.5 Flash across Technical Fit, Compliance Readiness, and Capital Efficiency. Dynamic State Injection: Operates with runtime awareness of team topology via fervo_state.json, ensuring tasks are assigned based on actual domain expertise. Swarm Orchestration: Decomposes complex grant applications into sub-tasks, routing them to human operators (Tech Lead, COO) and autonomous sub-agents. Impact By moving from "generative text" to "agentic orchestration," fervoAI Treasury Agent allows teams to focus on building while the infrastructure handles the hunt, the lock, and the deployment of federal opportunities.