Live tool
Paste an applicant, proposal, and foundation strategy. The tool restates the claim in one sentence, then returns a first-pass signal score, review route, board line, evidence, funder risks, and next actions. It is built for staff triage before a human grantmaker makes the call.
Calder Ridge is a fictional composite organization created for this demonstration. Any resemblance to a real nonprofit is coincidental.
The claim
Recommended next step
First-pass signal for staff triage. Not a decision, and not a measure of the applicant.
The score summarizes the balance of visible evidence against funder risks, as a triage input to the route.
Model route pending
Board line
The board line will appear here after the API reviews the grant context.
Review discipline
Every review answers the six questions of a disciplined first pass.
Questions 3 and 5 share an answer on purpose: a well-formed diligence request names the thing that would strengthen the claim.
Responsible AI guardrails
This tool will not make the funding decision. That belongs to people who are accountable for it.
It will not score an applicant's mission or worthiness. It reads one proposal against one strategy and reports what the evidence supports.
It will not replace a program officer's read of the people, the relationships, or the context that never appears in a written proposal.
It will not verify claims against outside sources. It reviews only what you paste. A high score means the argument is well evidenced as written, not that the facts have been checked.
It will structure the evidence, name the risks that optimistic language covers, and produce diligence questions a reviewer can send the same day. It makes the reasoning behind a first pass visible, so a human can defend the call to a board.
Why funders should care
Automating grantmaking is the wrong goal. This tool makes early review judgment visible, testable, and easier to defend.
The model is asked for evidence, risks, and next actions, not a summary and not praise. A grants platform should spend more intelligence where judgment matters and less where the task is repeatable.
Use the strongest model path for high-stakes review, contested evidence, and board-facing recommendations.
Use balanced production review for everyday summaries, comparisons, diligence questions, and staff workflows.
Use fast screening for eligibility, missing fields, routing, and duplicate intake triage.
Built by Wayan Vota
I'm Wayan Vota. I've spent three decades raising institutional funding on both sides of the table, as a capture and proposal lead winning more than $348 million from foundation, government, and corporate funders across 20+ countries, and as a reviewer deciding which proposals deserved it.
I built this tool because the AI now helping thousands of applicants write smoother proposals is erasing the signal funders used to read in the writing itself. Review judgment has to get sharper on the funder side, and this is what I think that looks like.
If you run grantmaking operations and want to talk about it, find me on LinkedIn.
Contact Wayan on LinkedIn