Your grantees are doing transformative work. But their impact gets buried in mismatched reports, inconsistent frameworks, and data you can't aggregate.
Sattva turns every grantee update into structured outcomes—automatically mapped to your foundation's impact framework.
Theory of Change
Outcomes Tracked
Define what matters. Sattva maps everything to your framework automatically.
Just got the Duval County pilot data back, we hit 94% target dosage! @Sattva
Great — a few questions for you:
Your grantees post in Slack. Sattva listens and asks clarifying questions—2 minutes, not 2 hours.
Ask questions across your entire portfolio. Get answers in seconds.
Duval County: 2,700 students served, 94% meeting recommended reading dosage
Gates Foundation
Improve Early Literacy Outcomes
Overdeck Foundation
Evidence-Based Scaling
Every grantee update is automatically translated into your framework—no manual extraction.
At its best, philanthropy is a catalyst for moral imagination. Philanthropic capital exists to fund new ideas, build new institutions, and lower the cost of social innovation by subsidizing risk.
Therefore, philanthropy is fundamentally entrepreneurial in spirit. Founders turn to venture capital when they want to pursue innovation in private goods. They should be able to turn to philanthropy when they want to pursue innovation in public goods.
“Social action is usually a slow process. Foundations by stepping in can speed up the process, acting as society’s passing gear.” Paul Ylvisaker, 1989
We urgently need this “passing gear” engaged. This era is marked by a chasm between the ideals we hold for our institutions and the realities people experience. Public confidence in American institutions has collapsed to historic lows. Only 28% of Americans say they have high confidence in major institutions, down from over 40% two decades ago.
The philosopher Hubert Dreyfus warned of two responses to this kind of drift: cynicism about our ability to change anything at all, and a narrow rationalism that reduces every problem to optimization. Both lead to the same place — forgetting that ambitious public action has shaped this country within living memory: community colleges, public libraries, national parks.
Philanthropy is the natural vehicle for restoring faith in our institutions, but to play that role well, it needs shared infrastructure and practices for measuring and funding what works.
Historically, philanthropy has lacked shared infrastructure because measuring impact is hard. Big bets are inherently risky, long-horizon, and hard to measure. Funding such initiatives works better when decision-makers share common practices for where to invest, how to track progress, and how to learn from their portfolios.
Over the past three decades the venture ecosystem built this infrastructure: standardized term sheets, stage gates, portfolio metrics. Philanthropy hasn’t built the equivalent for public goods.
Measurement has been fragmented — for many years, the field faced a false choice between vanity metrics and expensive randomized trials. Funders and operators lack a common framework for impact. And the feedback loops that work in private markets do not transfer easily: in public goods, an organization can create enormous value and still fail, because public value is not captured by the entity that creates it.
For these reasons, impact data does not emerge organically. It has to be constructed intentionally.
Now is the time to equip funders with portfolio intelligence. Funders need to define and track what success looks like for early-stage bets on public goods. This is now possible because:
The measurement science is ready. Recent field scans have identified thousands of credible impact measures. The problem is no longer a shortage of measurement science. It is an implementation and translation gap — making those measures operational, accessible, and shared.
AI can serve as the translation layer. A grantee submits a narrative report; AI extracts structured performance indicators mapped to the funder’s framework. Different frameworks are not a problem when there is a translation layer between them.
The feedback loops can get faster. Impact data doesn’t have to arrive annually in a PDF. It can flow more frequently, enabling both sides to steer rather than just account for the past.
Portfolio intelligence for impact investors and foundations is the first step. Equipping funders with decision-quality impact data creates the basis for a real practice of philanthropic risk-taking and entrepreneurship.
The ability to place bold bets, learn quickly, and double down will allow philanthropy to operate more like a portfolio — building shared knowledge about what works and directing capital toward the ideas that matter most.
Over time, this kind of infrastructure can strengthen the entire impact ecosystem. When funders and operators share clearer signals about what is working, resources can move more quickly toward the institutions and ideas capable of creating real public value.
That’s what we’re building. We’re still early. If this resonates, we’d love to talk.