For: development teams (or the one overworked person who is the development team) drowning in prospect research and first drafts.
What you get: a research-summary workflow, drafting templates grounded in your real program data and voice, a review path that keeps a human's name on every submission, and the training to run it without us.
For: organizations sending the same appeal to everyone because segmentation never got set up.
What you get: segment architecture in your existing CRM/email stack, reviewed AI drafting for appeals, thank-yous, and updates, and the guardrail that matters — personalization from data donors knowingly gave you, nothing scraped.
For: teams that spend the week before every board meeting reassembling the same numbers.
What you get: program data flowing into board-ready and funder-ready summaries with a human review pass, plus documentation of where every number comes from — because a generated statistic nobody can trace is a fabricated one.
AI that talks to beneficiaries unsupervised, generated impact statistics (fabricating outcomes is the sector's cardinal sin), donor-data enrichment that donors would find creepy if described plainly, and mass-generated grant applications — funders are already deploying detectors and irritation in equal measure. If a build cannot be described honestly in your annual report, we do not ship it.
That is the design center. Builds assume turnover: documentation a new volunteer can follow, tools on the org's accounts (never a staffer's personal login), and training included in scope. The one-page AI policy we set up mirrors the practice our network documented for churches — approved tools, a data rule, a named person to ask.
Small fixed-scope projects, priced per project after the free scoping call — nonprofit budgets get a straight number before any commitment, and grant-fundable scoping documents are part of the deliverable when you need to raise for it. If the honest answer is "claim your vendor discounts and skip us," the call ends there at no cost.