Kindora is building the trust layer for social sector capital: every organization legible to every funder, every introduction vouched, so money moves to the people closest to the problem. Today that starts with fundraising software that nonprofits and social enterprises use, and that foundations buy for the organizations they back.

Meet Justin

I'm Justin Steele, Kindora's co-founder and CEO. Before the product and the numbers, you should know who is asking for your trust.

I got here partly because programs aimed at kids like me worked. The National Society of Black Engineers helped make me an engineer. Management Leadership for Tomorrow helped carry me to Harvard for an MBA and MPA. I know what well-aimed opportunity feels like from the receiving end, and I've spent my career trying to aim it better: Bain/Bridgespan consultant, Year Up deputy director, then ten years at Google.org directing about $700M in philanthropy across the Americas. Today I serve as a trustee of The San Francisco Foundation. My wife Sally and I co-founded the family camping nonprofit she leads, Outdoorithm Collective, where Kindora was born. Funder, grantee, builder, beneficiary. I'm a mixed-race Black man who has sat in every seat at this table.

Google eliminated my role in 2024, after a decade. I've written publicly about that season and what it taught me: a mission that lives inside someone else's structure is only as safe as that structure's incentives. So this time I built the structure first. Kindora is that decision, incorporated. A Public Benefit Corporation with its mission locked in the charter, raising from the community it serves, on terms that can return your capital without ever demanding we sell.

I wrote the code, designed the data layer across 250K+ funders, closed the first enterprise contracts, and answered the support tickets. That is the bet at the center of this company: AI has collapsed the cost of building, so the people closest to the problems can finally build the tools their fields need. Kindora has one full-time person today. This raise funds the team. But what one person built is your proof that the bet works.

Someone is going to prove there's a different way to build and own technology for the social sector. I've sat on every side of that problem. Here's where it started.

Why Kindora exists

It started late one night in our Oakland living room, after the kids were asleep. I was hunting for funders for the family camping nonprofit my wife and I run. We had about $33K in the bank and needed $9K for tent heaters. The platform I was paying thousands a year for had just handed me 2,400 funder "matches" that would have taken a year to sort through. I had spent ten years directing philanthropy at Google — and I could not find nine thousand dollars.

So I built an AI that reasons like a program officer instead of a search engine. In its first test, 90% of those matches vanished as false positives. Near the top of what remained was a foundation run by a professor I had known for years but had never connected to our work. Within 24 hours we had a meeting with its president. Other nonprofit leaders saw it and asked the same question: can I use this? Kindora is the answer.

The problem

Americans gave $617 billion to charity last year — a record. Getting to your share of it fails in two places.

First, you can't see the money. Most private foundations report they only fund organizations they have already chosen; about one in ten even has a website; the public grant records that do exist typically arrive eighteen months to three years late. And the fastest-growing pool isn't public at all — donor-advised funds now hold $328 billion and moved $64.6 billion out last year, disclosed only in aggregate across 1,512 sponsor filings covering 3.59 million accounts, not one of which names the donor behind a gift. You can research a foundation. You cannot research a DAF.

Then, you can't reach it. Money moves through relationship networks, and those networks are sorted by geography, race, class, and institutional power. For most nonprofits the capital is already somewhere inside their own network — they can't see who holds it, and even when they can, they have no credible way in. Proximity to the problem and proximity to the money are almost never the same thing.

The tools that could bridge either gap — AI grant platforms at $299 to $999 a month, donor-intelligence subscriptions starting around $4.5K and running to tens of thousands a year — cost more than most of these organizations can spend on anything. That's the gap Kindora was built to close: visibility into who holds the money, then a credible path to them.

And it is getting harder. AI now writes applications at scale. Funders report volumes doubling or tripling, and some have stopped taking applications at all. As doors close to everyone a funder doesn't already know, someone has to make the organizations closest to the problem visible and trusted. That is what we are building: the trust layer for social sector capital, so money moves to the people closest to the problem.

What we built

Kindora does the work of a development office. Ask for an outcome in plain language and Kindora returns structured, sourced results: ranked funder matches, drafted letters of intent grounded in each funder's actual giving, warm paths from your board to the people who write checks, and prioritized donor lists with outreach plans. Every result cites its sources.

Proof from two real customers:

• For Outdoorithm Collective, the nonprofit my wife and I co-founded, one grant opportunity that used to take about 40 hours went from discovery to submission in about 90 minutes. We raised $100K in our first year from the prospecting list Kindora created and the application drafts it provided to us.

• In a $32K paid engagement for an unaffiliated Bay Area education fund, Kindora analyzed 33,762 donor contacts and evaluated 1,210 institutional funders, rating 110 a good or ideal fit, to produce a board-ready cultivation strategy.

We are now building the next two layers. The funder workspace, in beta since October with no funders in it yet, lets a foundation find and diligence the organizations doing the work it funds. And Introductions, being built now, gives a network (a funder's grantees, an association, a fellowship, a conference) two-yes introductions between members who have a reason to talk. The same data layer serves every side.

The best diligence is to use it yourself — kindora.co is free to start. If you'd rather watch than sign up, this is the product, start to finish, in one take.

That's a real workspace, not a mockup: every screen in it is the production application, and the narration is unscripted.

Search is the wedge, not the moat

AI search is commoditizing, and anyone can put a basic chat box on a grants database. What is defensible today is the live data layer (250K+ funders based in 110 countries, 9.3M grant records, 51K+ open and upcoming opportunities, and 95K+ funder websites monitored on a rolling schedule) and the workflow that carries a nonprofit from discovery through submission. That data layer can become a product in its own right: third parties can now reach it through metered API access, so the asset that powers the app could also become a business other builders pay for. What compounds from here is outcome data: organizations draft with us, then tell us which applications were funded and which were declined, so we learn what wins, where, and why. That exists in no public filing, and nonprofits rarely move once their history lives in one place.

Grant databases are a crowded market, and investors are right to ask what is different. Three things. A proven buyer: foundations already buy grantee cohorts from the leading incumbent, whose individual subscriptions list at $3.6K to $12K a year with cohort pricing unpublished; Kindora prices a seat at about $500 a grantee a year, and seven funders have bought since June. A different channel: nonprofits find Kindora inside Claude and ChatGPT, not through an ad, with 220,000+ agent calls since April and under $500 of ads ever. A different product: the incumbents serve one side at a time, discovery and drafting for nonprofits or due diligence for funders, while Kindora is building the connection between them, nonprofits legible to funders and vouched introductions. We compete on execution and distribution, not on the idea.

Traction

As of this writing:

• 2,500+ organizations have joined Kindora; 119 pay for their own seats, and 80% of all who ever paid still pay. Under $500 spent on paid ads, ever, and no paid channel drives growth.

• About $204K of annual recurring revenue is under contract: $74,238 self-serve, $49,620 from funders who have paid, and $80,000 from two funder contracts signed and invoiced but not yet paid. That is $124K from customers who have paid. Services are counted separately.

• Self-serve recurring revenue grew about 7× from February to September, from $867 to $5,901 a month, measured from Stripe invoice lines net of discounts.

• $42K of donor-intelligence engagements at 75 to 80% gross margin, contracted through True Steele, our founder's consultancy, while the line moves into Kindora PBC. These are one-time engagements, so they sit outside the recurring figure.

• Anthropic featured Kindora as a customer story. Forbes covered us in June. AWS published our Social Entrepreneur Accelerator story in August, which also puts on the record that Deloitte is providing strategic and operational support as we scale.

• Funder-pays is working: seven funders buy Kindora for the organizations they back. Five have paid: a Bay Area poverty-fighting philanthropy (20 grantee seats), a national fellowship funder (30 fellow organizations), a family foundation that bought twice, a spend-down family foundation and a conservation capacity program. Two more are signed and invoiced: a national technology-and-society funder (74 member organizations) and a major Bay Area community foundation (75 grantees).

How we make money

Funder-pays is the spine, free is the funnel, and networks are the reach. Kindora acquires nonprofits free and self-serve, then monetizes at scale by selling sponsored access to the funders who already back them, and one contract onboards 20 to 80 nonprofits at once.

Three lines are live today. Self-serve subscriptions at $25 to $199 a month for nonprofits and $399 a month for consultants are the volume line and the funnel. Funder-pays contracts, mostly $10K to $50K a year per funder, are ahead today: seven funders are under contract, and the payer brings the users with them. Metered agent and data access at published per-lookup pricing is the newest and smallest line: $0 today, outside our base case and our 18-month milestones; the funded plan assumes it starts in 2029, the upside case in 2028.

Why a funder buys, and whether it renews, are the two questions this model turns on. A funder pays about $500 a grantee a year, a capacity line item, with quarterly reporting on its portfolio's use of Kindora (built; the first report has not yet been delivered). All seven contracts were founder-sold, verbal to signature in one to two months. Renewal is the open question: the first renewals come due in 2027. So far, 16 of the first 23 sponsored grantees use Kindora, 15 of them in the last 90 days, and one funder has bought twice. Our base case assumes only one of the seven renews. The upside case assumes 85%; at 70%, its 2030 revenue falls about 4%.

A fourth line is being built now: networks. Any network (a funder's grantees, an association, a fellowship, a conference) can pay for the room where its members meet: two-yes introductions between people with a reason to talk, the network's own questions in the matching, and a report on whether its members connected. Members join free, always, and every member who joins makes the next good introduction more likely. Pricing is proposed at $2,500 to $5,000 per network a year and untested, and no introductions revenue is in any projection.

One economic note worth stating plainly: we sell credits, not seats. As inference gets cheaper, credit prices hold while cost-to-serve falls, so cheaper AI widens margins instead of compressing them.

The market underneath it is 1.9 million US nonprofits, roughly 80% of them priced out of professional fundraising tools by our estimate, plus about 22,000 foundations that grant $1M or more a year. That is the US alone. Kindora is already international, with no international marketing behind it: our database covers funders based in 110 countries, and more than 350 organizations outside the US have joined, from more than 50 countries, including paying customers in Canada, India, Bangladesh, Peru and Italy. Our plan counts none of that. Two hundred foundation contracts at a $25K average is $5M of ARR and puts Kindora in front of roughly 10,000 nonprofits. That's the shape of this business: it gets large by reaching tens of thousands of small organizations, not by charging them more.

Our plan is built to reach $10M or more of recurring revenue by 2030, driven by free-tier distribution, customers moving up-market as they grow, and funder-pays cohorts. That is a projection, not a guarantee; our base case and every assumption behind it are in the pitch deck's appendix and the data room.

Why now

AI changed what one person can build, and AI marketplaces changed how software reaches customers. Kindora ranked #5 in Claude's connector directory at launch, and our connectors are now live in both the Claude and ChatGPT directories. Our MCP infrastructure has handled more than 220,000 real external calls since April, now about 1,500 a day. Until recently those calls were pure top-of-funnel: usage we convert to paid accounts on kindora.co. Third-party developers can now also reach our data layer through metered API access, priced per lookup. To be precise about what that means: it has earned $0 so far, and none of it is in our base case or our 18-month milestones. The direction is deliberate; the revenue is not yet proven.

Where this goes

Here is the sector we are building toward. Every organization doing real work is legible: what it does, who it serves and what it has achieved, readable by any funder in minutes instead of found by accident over years. And trust can travel. Today much of it runs through existing relationships: 71% of US private foundations take no unsolicited requests, and at the largest donor-advised fund sponsor, 77% of grants went to charities the donor already supported. Organizations outside those circles are hard to see and harder to vouch for. In the sector we are building, a funder in New York can find, and trust, a leader in Fresno it would never have met, because someone they both trust said yes to the introduction.

Picture every grantee cohort, association, fellowship and conference as a room where the right people meet. Picture a funder who closed its open call because AI buried it in applications, able to see again who is doing the work. If one dollar in twenty of the $617 billion Americans give each year reached strong organizations funders could not see before, that is about $30 billion a year moving to the people closest to the problem. That figure is an illustration, not a forecast, and none of it is in our projections. It is the reason this company exists.

We are building it in order. Funders legible to nonprofits is live, with seven funders under contract. Nonprofits legible to funders is in beta, with no funders in it yet. Introductions opens with its first networks in November. Trust has always traveled through people: at Google.org, we found grantees through people we trusted. Kindora makes that path findable for everyone else, with two yeses, a named vouch and consent at every step. That is the company this round invites you to own a piece of.

Why a community round

A grant funds a program; equity funds ownership. Last September I sat at my desk late at night, fifteen clicks deep into Vanguard's withdrawal screens, and moved $100,000 out of our retirement to keep going. I had spent a decade directing philanthropy at Google.org, yet when I went looking for $350K to build technology for the sector I had served, its capital stack had no instrument for a company like this. VCs and private equity came knocking instead. The first believe-in-you check came from Camelback Ventures, a $50K SAFE.

This round is the resolution of that story. Mission tech has been stuck between venture capital that needs unicorn economics and grants that rarely fund durable products. Kindora is a Delaware public benefit corporation built for nonprofits and funders, and this round invites that community to own a piece of the infrastructure it uses.

If you've ever thought there should be more than one way to build and own a company like this, this round is how that gets built. We'd be glad to have you.

Where I've said this out loud

If you'd rather hear it than read it, these are the conversations where the case for Kindora got tested by people who know the sector.

1. People in Common with Jama Adams (September 2026). Seventy minutes with the person who helped grow the Giving Pledge, on conviction, belonging, why Google's 1% was a founder's letter and not a law, and why this round is open to anyone. The most complete version of the story I've told anywhere.
2. The Do One Better Podcast with Alberto Lidji (August 2026). Why better information won't change what funders fund, and why trust is the layer we're building next.
3. Forbes: Grants fund programs. Ownership funds the future. (June 2026). Why the social sector should own the AI tools being built for it.
4. Anthropic customer story (August 2026). How one person built the platform with Claude Code, and what the case study leaves out.

The terms, in plain English

We are raising on a SAFE with a valuation cap (Wefunder's template, customized by our counsel) with one added feature: a capped revenue-share right. The first $1M invested on Wefunder receives a $10M valuation cap, the same terms as our anchor investors; investments after that are at a $12M cap. $10,000 at the $10M cap converts into about 0.1% of the company as capitalized before this round's SAFEs. The other SAFEs in this round and new money in a priced round dilute that; the option pool is already counted.

Most startup investments have one way to pay you. This one has two. The SAFE converts per its terms in a future priced financing and carries the liquidity-event rights stated in the contract. Separately, once Kindora passes $1M in annual recurring revenue, 3% of adjusted gross revenue (cash receipts less refunds and taxes) is distributed quarterly, pro rata across the investor pool, until the pool has collectively received 1.5x its investment. That is a second possible path to a return, not a promised yield: for scale, at $5M of annual revenue the whole pool would receive $150K that year, subject to the annual caps described in the Agreement.

Which path pays depends on which future arrives, and neither path nor its timing is guaranteed. Whatever our revenue, after three years from your investment date, if the agreement is still outstanding, you can choose to convert it into common stock at the cap price, which ends any remaining revenue-share payments. If Kindora never passes $1M ARR, the revenue share never starts, and the SAFE is your only path to a return. The final contracts and the Form C, not this summary, control the terms.

If we raise a priced round, you convert to preferred stock at your cap (or the round price, if lower), and revenue-share payments stop. If we're acquired or go public, you are owed the larger of what is left of your 1.5× or your investment's value as common stock at the cap price; the 1.5× is paid only from proceeds available after debts and any earlier preferred stock, alongside other SAFE holders, and any unpaid part becomes common stock, which may be worth little or nothing. If we stay independent past $1M ARR, 3% of cash revenue (receipts less refunds and taxes) is paid to the pool until it reaches 1.5×, and the SAFE stays outstanding. If we shut down, you are owed what is left of your 1.5× after debts and any earlier preferred stock, shared pro rata if the money runs short. Not a guarantee.

The Agreement will expire and terminate (without relieving the Company of any obligations arising from a prior breach of or non-compliance with this Agreement) upon either (i) the issuance of shares to the Investor pursuant to Section 10(a), Section 10(b) or Section 10(d); or (ii) the payment, or setting aside for payment, of amounts due the Investor pursuant to Sections 10(b) or Section 10(c), but for the avoidance of doubt, not pursuant to Sections 3 or 4; provided, however, that Section 5, the last paragraph of Section 10(d), and Section 13 shall survive any such termination. See the investment contract for full terms.

Why a $10M cap

Fair question at ~$204K of ARR under contract, $124K of it from customers who have paid. For context, SAFE caps at this stage are priced by stage and raise size, not revenue multiples: Carta's 2025 data puts the median valuation cap for rounds raising $250K to $1M at $10M, mostly for pre-revenue companies. That makes this cap the market median for a raise our size, and roughly half the median of a priced AI seed round. The cap prices what has already been de-risked, not today's subscriptions: a production product the company owns outright, the live data layer, 2,500+ organizations and 119 paying organizations acquired with no paid acquisition channel, seven funder contracts, and distribution inside both Claude and ChatGPT. What remains unproven is repeatable selling and whether funders renew; the hires this raise funds own both. The first $1M also invests at the same cap as our anchors; the community does not pay a premium over the insiders.

Use of proceeds

On a $1M raise, Wefunder's 7% fee leaves roughly $930K before legal, accounting, and other offering costs; the Form C will show the final numbers. The core product and data layer are live, so we are not raising to find out whether the product can be built. This capital funds go-to-market: roughly 44% to two BD/AE hires and an account manager, roughly 24% to the cost of serving customers (AI inference, data pipelines, hosting), roughly 23% to founder and operations, and roughly 10% to legal, compliance, and buffer, plus working capital to serve enterprise contracts well. Product stays founder-led, so the modeled plan needs no engineering hire. And to answer the question every founder gets asked here: yes, operations includes a modest salary for me, so this company has a full-time founder.

Put plainly, this raise is how Kindora stops running on one person.

Team

I built the core product, and the company owns its intellectual property. My co-founder Karibu Nyaggah, a Harvard MBA sectionmate who led AI transformation for the Meta Ops team, has moved to a strategic advisor role and advises on strategy, go-to-market, and operations. Karibu and I first met in 2003, at Harvard Business School's Summer Ventures program, a week-long immersion designed to increase diversity in business leadership.

Two people who brought me into this work now advise Kindora on our Strategic Advisory Council, and both hold equity as advisors.

Gerald Chertavian, who chairs the council, founded Year Up and led it as CEO for 24 years, growing it to 30 cities and more than 45,000 young adults. Today he is a Senior Lecturer at Harvard Business School. I first heard him speak when he came back to HBS for a social enterprise panel, and I still remember meeting him on the fifth floor of 93 Summer Street in Boston and hearing him say he bleeds blood for young people. He wasn't like any HBS alum I knew. I interned at Year Up's national headquarters after my second year of graduate school, joined full time afterward and became a deputy director. Gerald advises us on growth, capital structure and enterprise partnerships, and he invested in this round.

Susan Colby, a founding member of the council, was a partner on the founding team of The Bridgespan Group and led its San Francisco office. I was an associate consultant at Bain in Atlanta, working long hours, traveling constantly and struggling to find my footing, when Susan and the San Francisco office offered me a transfer. Bridgespan was a gift: it showed me I could keep the rigor of management consulting and spend it on the social sector. Susan later ran the Stupski Foundation and co-founded Imagine Worldwide, and she advises us on growth strategy and funder relationships.

Data stewardship

Our customers trust us with donor data. Every organization's data is isolated to its own tenant. We do not pool customer data across organizations, and we do not train shared models on it.

If you invest

Expect quarterly investor updates, an annual financial summary, and our annual public benefit report as a public benefit corporation.

The risks, honestly

Company-specific first:

• Free-to-paid conversion is still being proven at scale.

• Claude is an important marketing channel we do not control.

• Our grant-outcome data needs time to mature.

• The team is currently concentrated in me.

• Networks and introductions are being built now; their pricing and uptake are unproven, and none of their revenue is in our projections.

• The grant-database category is crowded, with well-funded incumbents and new AI entrants, and the leading incumbent sells grantee cohorts to foundations too. Our wedge is price per seat, the agent channel and the connection between the two sides; we compete on execution and distribution, not on the idea.

• Funder renewal is unproven. Seven funders are under contract and the first renewals come due in 2027. Quarterly portfolio reporting (built; first delivery pending) is meant to argue each renewal with usage, and the account manager this raise funds owns it. Our base case assumes one of the seven renews.

• If AI simply helps everyone submit more, funders get buried and the sector is worse off. We built the brake before the accelerator: Kindora tells an organization when it isn't a fit and suppresses low-fit matches instead of maximizing applications. Our bet is that the problem was visibility rather than volume, and we will be measuring how funders actually respond as usage grows.

Structural:

• This is patient, long-horizon, illiquid capital. There is no secondary market.

• A return depends on revenue growth or a liquidity event that may not occur.

• Invest only what you can comfortably afford to lose.

And one risk is a choice rather than an accident. Our first check came from a venture fund, and venture investors are in this round. What we've built away from is dependency on traditional high-growth venture capital — growth funded by revenue, no Series A on the roadmap unless scale genuinely requires one. Know that a crowdfunded cap table can narrow traditional financing options later. We accepted that trade for independence and community ownership. Weigh it before you invest.

What I can tell you is that the problem is real, I have lived it, and early customers show that nonprofits and foundations will pay. The product is built. We're raising to sell it.

Other Helpful Resources

Anthropic Customer Story

Forbes - Ownership Funds The Future

AWS Social Impact - Kindora and the Social Entrepreneur Accelerator

People in Common Podcast - Coding Belonging with Justin Steele