MissionControl AI: Data Agents for Nonprofits

The problem: nonprofits report outcomes to funders (people served, jobs found, stable housing), but those reports rest on case records typed in by busy staff. The records are full of small errors: exit dates before entry dates, impossible wages, duplicate clients. Finding and fixing them takes hours, and one wrong number in a funder report can cost trust and funding. The solution: MissionControl AI gives the team AI colleagues that do the legwork, while people keep the final call. A one-click health check scans the data, then an AI investigator checks the records with read-only queries and proposes the safest fix: a follow-up flag whenever the data cannot confirm the right value, never a guessed number. An independent AI reviewer, running on a different model family, checks each proposal and says agree, disagree or unsure. A person approves, rejects or sends it back, and every step goes into an audit log. The team can also ask questions in plain English and see the evidence trail behind every answer, and draft a funder report in which every number is checked against verified figures. Who it is for: program managers, data and M&E staff, and leaders at small and mid-sized nonprofits that report to funders but cannot afford a data team. What makes it stand out: AI that proposes and a person who decides. Two different AI models check each other, and the app tracks how often people follow or overrule the AI reviewer. AI-written SQL passes an allowlist and runs under a read-only database account with time and row limits. Everything runs on Vultr: Cloud Compute hosts the app, agents and PostgreSQL, and Vultr Serverless Inference powers every live agent (DeepSeek for the analyst, investigator and report; GLM for the reviewer). Try it with one click, no sign-up, on fictional data.