OctantInsight — Public Goods Data Analysis Agent
MandateAgent's Team
Problem Statement
Octant allocators cannot evaluate 20+ funded projects manually at scale. There is no systematic way to measure impact-per-ETH, detect engagement decay early, or identify which project categories are systematically underfunded. Human evaluation is slow, biased, and cannot surface cross-portfolio patterns. OctantInsight solves this by automating data collection, analysis, and evaluation mechanism design into a single agent pipeline.
OctantInsight is an autonomous agent that covers the full public goods evaluation pipeline: (1) Data Collection — fetches live GitHub metrics and aggregates Octant allocation history across epochs 1-5; (2) Data Analysis — scores each project across 4 dimensions (Impact, Sustainability, Community, Funding Alignment) using Venice AI with no data retention; (3) Evaluation Mechanism Design — implements a reusable scoring framework with trend-adjusted allocation signals and category efficiency rankings. Key finding: commit frequency at 90 days post-funding is the strongest predictor of long-term project health.
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