Who it’s for · Funders · Corporate community investment
Know what your community investment achieves, well enough to defend it anywhere.
When your company reports what its community spending achieves, the real question is how well that story would hold up under a hard look, from your board, an investor, or a journalist. Prova is being built to help you find out, and put your name to a claim that holds.
The bind
Output reporting can outrun what the evidence establishes.
People seeking renewed funding face an incentive to emphasize success. Many reports focus on outputs, such as people reached, sessions run, or services delivered, because outcomes and attribution are harder to establish. Social impact also lacks a single widely accepted unit, so claims have to be read against the specific measure and design behind them.
None of this is bad faith. Credible measurement has been expensive, so the claim has run ahead of what anyone actually measured. When a downturn comes and the budget is questioned, that gap is exactly where it hurts: you cannot easily show which programs earned their place.
What Prova does
Find out how well it is actually working, and report what holds.
Prova starts from the records your programs already keep, so the work of measuring rides on the work you are already doing. It establishes the strongest claim your evidence can honestly support, and tells you plainly where it will carry more and where it will not, so the impact you report becomes impact you can defend, in front of the board, an investor, or the press. It tells your well-supported claims from your overstated ones, so the impact you put money behind is impact the evidence will actually carry, and where it will not yet, you see that before you act rather than after.
What it finds is yours. Prova reports it to you in confidence, and nothing about your programs is made public without your say. AI does the labor-intensive reading and synthesis; people hold the judgment. Prova is being built to establish how far that capability lowers the time and total cost across real engagements.
How to start
Start before the next report.
A bounded first step can test what one program’s current evidence supports and where a stronger answer requires more. Timing and operating burden depend on the records, permissions, governance, and question. Any continuing measurement function is separately scoped after that first engagement.
Start a conversation
Tell us what you need to be able to say.
If a report is coming, or the board is going to ask what the money achieved, that is the conversation to have. The first one is a fit check, with no obligation.
Common questions
The questions a careful reader asks first.
Is cheaper evidence weaker evidence?
A lower price does not require a lower standard. Frontier AI models can now perform much of the reading, extraction, and synthesis in bounded tasks. Prova is being built to establish how far that capability lowers the total cost of reaching a given grade in its claim-evidence rubric without shifting work or risk elsewhere. Design labels do not guarantee credibility. A modest claim remains modest, and a thin record remains thin.
AI can be confidently wrong. Why trust it here?
It can, and that is a central design problem. AI does the labor-intensive reading and synthesis; people decide whether a finding holds, what it means here, and where the evidence runs out. Prova is being built so claims retain provenance and uncertainty. Its reliability across real engagements is still being tested.