You collect the data; the AI writes the words. These automations turn the programs, indicators, entries, and stories you already track into narratives, reports, and tools, with your numbers passing through untouched.
Open AI Automations from the sidebar, directly under Dashboard. Most automations are data-driven: pick a program and the AI reads its description, theory of change, indicators, targets, and recorded entries. The richer your data, the better the drafts.
The flagship. It reads ALL your programs, every indicator's targets and actuals, and your story titles, then rolls them into one annual narrative: the need and your answer, the year in numbers, what changed for people, honest learning where targets were missed, and the year ahead.
This one document feeds the Annual Report app, grant applications, and board orientation. Run it after your year-end data entry is complete.
The AI button on the Predictions page. The Predictions page itself is free for everyone: it extends the data you have recorded across the year at the current pace, compares each indicator to its target, and labels it On pace, Slightly behind, or Behind with a projected year-end value. Those scores are transparent, computed in your browser from your own data, with the factors shown in plain view.
This brief turns those scored trajectories into a short, prescriptive action plan for staff and board: which indicators are on track, which are slipping, and the specific moves (delivery, data collection, or a target conversation) that would get a behind indicator back on pace before year-end.
Pick a program and get 4 to 6 right-sized indicator suggestions: a mix of outputs (prove delivery) and outcomes (prove change), each with a precise definition of what counts, a realistic data source, and target-setting guidance, plus a section on what NOT to bother measuring yet. Designed against the classic failure of over-collection.
From a program's description, the AI builds the full chain working backwards from impact: inputs, activities, outputs, outcomes, a one-sentence impact statement, and the risky assumptions your measurement should test first. Apply writes everything straight into the program's Theory of Change, ready to refine with your team.
Pick a program with indicators and recorded entries; get a plain-language brief for staff and board: what the numbers show against targets, what looks strong, what looks stuck, the possible explanations worth investigating (delivery, data quality, or the theory itself), and the one or two decisions the data suggests. Analysis without a statistician.
Reports one program against what was promised: each target and actual exactly as recorded, the honest story behind any variances, what you learned, and what comes next. Add accomplishments and context in the optional box for a richer draft. "We found X, so we adjusted Y" is one of the most persuasive sentences a funder can read.
A short survey people actually finish: 6 to 10 scaled questions mapped to a program's outcomes, one or two open-ended questions, a respectful consent intro, and guidance on which questions to ask at both intake and exit so you can measure change. Pairs with the Pre/Post Tracking page.
Write rough notes in a story's body on the Stories page, then pick it here. The AI shapes the notes into a publishable 150-250 word story with a real arc, the participant as the hero of their own change, and no invented quotes. Apply replaces the story body after confirmation, and every draft ends with a reminder to confirm written consent and consider changing the name.
AI drafts are writing assistance, not evaluation findings: review every draft before sharing. The Impact & Outcomes app is part of All In One Nonprofit.