Mission Log

Institutional fundraising requires precision. Success depends on preparation: identifying opportunities early, aligning teams effectively, and presenting proposals that match donor priorities. BD teams manage substantial operational work—maintaining opportunity trackers, developing presentations, adapting proposal language, conducting donor research, and coordinating internal processes. AI can handle routine tasks efficiently, freeing capacity for strategic work: relationship

nstitutional fundraising teams are under pressure. Budgets are tight. Proposal deadlines are nonstop. And competition for funding has never been fiercer. That’s why more NGOs are looking at data and automation, not just to save time, but to make smarter decisions about where to focus limited resources. Machine learning is one way to do that. It’s not futuristic or overly technical. In fact, many of the tools your team already uses are powered by machine learning, and the meth

NGO teams are not short on skill, purpose, or data. They’re short on time, staff, and energy. Every day, your team is responding to donor requests, coordinating with partners, drafting reports, updating project trackers, and trying to get a comms post out — all with one eye on the field and one eye on the budget. What’s broken isn't the mission. It’s the manual workflows. That’s where AI-powered automation using tools like Make.com , ChatGPT, and Claude can finally give you b