Grant and proposal writing

Answer exactly what the funder asked, with evidence

Your AI builds a funding application the way a development officer would: eligibility and rubric mapping first, a need statement with sources, a goals-to-activities chain, an evaluation plan, a budget that matches the narrative, and a compliance pass.

By Vander Labs. Works with Claude, ChatGPT, Cursor and Claude Code.

What your AI learns

• Maps every rubric criterion to the section that answers it
• Writes SMART objectives, an evaluation plan and a justified budget
• Runs a compliance pass on limits, formats, attachments and numbers

How it works

1. Eligibility and fit: Every criterion marked pass, fail or unclear; honest reframing or a different call if the fit is thin.
2. Skeleton from the call: The funder's headings in their order with limits at 90 to 95 percent, rubric weights mapped.
3. Need statement: One sourced statistic, one local data point and one human example, no statistic pile.
4. Goals to activities: Goal, SMART objectives, activities and countable outputs in a visible logic chain.
5. Evaluation: Indicator, baseline, target, source and frequency per objective, with an owner.
6. Budget and justification: Lines grouped as required, each with its calculation, and every line present in the narrative.
7. Timeline and capacity: Period-by-period activities and milestones, team qualifications, partners only if agreed.
8. Risks and sustainability: Three real risks with mitigations and what continues after the grant.
9. Compliance pass: Limits, formats, signatures, consistent numbers and the abstract written last.

Limits and safety

• Never invents data, partners or letters of support; unconfirmed items are marked to confirm.
• Not legal, tax or accounting advice; flags where a professional should check.

Topics: grants, proposals, nonprofit, fundraising, budget