seenCAPITAL

She was always there.
The world wasn’t looking.

There are 340 million women running businesses in the informal economy. They have customers, revenue, and ambition. What they don’t have is a capital system that can see them. That’s what this company is for.

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Seen Capital
Summary Why Seen Investor Deck Capital Thesis Exit Thesis Not Microfinance NGO Partnership NGO Directory Jurisdictions Self-Optimising Model
Live Demo
seenCAPITAL
Series A · March 2026 · Confidential
Seen Capital
Seen Capital · Technology Company · Founded 2026
Hundreds of millions of people have never had access to capital. That is not a tragedy — it is the largest untapped market in global finance. AI eliminated the cost barrier that kept it locked. We built the infrastructure that opens it.
7
AI agents — fully automated investment pipeline from intake to agreement
6
Operating geographies with live NGO partner deal flow
Demo
Live pipeline available now — request a demonstration
Hundreds of millions of people. Hundreds of billions of dollars. A market that has been structurally unreachable — until now.
01
AI eliminated the barrier. A seven-agent AI pipeline handles every stage of the investment process — intake, research, scoring, interview, decision, agreement, monitoring — in any language, at any scale, at a cost structure no human team can match. It is working. You can see it today.
02
The distribution is proprietary. Fourteen years of community relationships across six geographies, formalised into an NGO partner network that feeds the pipeline with pre-qualified candidates. This took fourteen years to build. It cannot be bought or replicated.
03
The market is enormous and uncontested. Every nano-business run by people in emerging markets who have never had access to equity capital. No competitor exists. No competitor can exist without the community trust that took us fourteen years to earn.
Private & Confidential · Not for Distribution · March 2026
The Core Thesis
The Largest Untapped Market
in Global Finance.
And the Only Infrastructure That Opens It.
Hundreds of millions of people have never had access to capital. The market they represent is worth hundreds of billions of dollars. Every previous model has been structurally unable to reach it — the cost of deploying capital exceeded the returns it could generate. AI eliminated that cost. Seen Capital built the infrastructure. The fund is how we prove it. The platform is how we scale it.
What We Have Built
A seven-agent AI pipeline that handles the complete investment lifecycle — candidate intake, identity and revenue research, scoring, interview, investment decision, legal agreement, and ongoing monitoring — in any language, via WhatsApp and mobile money, at a cost per investment that is two orders of magnitude below any human-managed equivalent. We can process a candidate in Kinyarwanda, score her at 92/100, deploy $900 to her MTN Mobile Money account, and begin monitoring her KPIs — in 48 hours, with no human intermediary. This is not a concept. It is working now. A live demonstration is available.
Why It Is a Platform, Not a Fund
The pipeline that manages 500 portfolio companies in Fund I manages 5,000 in Fund III at comparable marginal cost. It licences to any operator who wants to deploy capital in any geography using our infrastructure. It sells to any DFI, development bank, or impact asset manager that wants AI-managed portfolio infrastructure without building it themselves. The fund is the first customer of the platform. The platform's market is the entire $300B+ impact investing industry — and every institution currently failing to reach the last mile. We are building the rails. We are also the first train.
The Comparable That Matters
Stripe did not build a payments company. It built the infrastructure that made payments trivially easy for every business on the internet — and charged a fee each time. Seen Capital is building the infrastructure that makes equity investment trivially deployable to any nano-business, in any language, anywhere in the world — and earns management fees, carry, and licensing revenue each time that infrastructure is used. The TAM is not Fund I. The TAM is every dollar of capital that has never reached the last mile because the infrastructure to get it there did not exist.
The Problem We Solved
The Biggest Market
on Earth —
And Why It Was Locked

Hundreds of millions of people run businesses that generate real income, serve real communities, and have never had access to a single dollar of equity capital. The venture capital and development finance industries have known for decades this market exists. They could not reach it — not for lack of desire, but for lack of a cost structure that made it viable. That constraint no longer exists.

The management cost barrier. A human portfolio manager can manage 8–12 companies. A 500-company nano-business portfolio requires 40–60 professionals — at salaries that consume every basis point of return at this ticket size. The economics have never worked. Every serious player in development finance has known this. None of them could solve it without AI.

The language and geography barrier. Serving a woman in Naryn Oblast, Koraput District, and Namche Bazaar simultaneously requires Kyrgyz, Odia, and Nepali fluency, plus physical presence or expensive local staff. The coordination cost alone makes the model non-viable. Until a system can conduct a 40-minute intake conversation in any language via WhatsApp.

"Every dollar of impact capital that has failed to reach the last mile failed for the same reason: the cost of getting it there was higher than the return it would generate. AI just eliminated that cost."

The instrument problem. Microfinance tried debt. It created dependency and consumed value through interest. Grant capital tried aid. It created dependency of a different kind. What these businesses need — and have never had access to — is equity: a partner who shares the upside, provides ongoing support, and has an incentive aligned with the business's long-term survival.

The measurement and compliance gap. DFIs and impact investors require impact measurement, KPI reporting, and compliance infrastructure. The woman running a savings group in Musanze does not have an accountant. She has never filed a tax return. The compliance overhead of serving her has always exceeded the capital value of investing in her. Until the compliance infrastructure itself is AI-generated.

"The pipeline generates impact data, KPI reports, and compliance documentation automatically — as a byproduct of portfolio monitoring. The overhead that made this market inaccessible is now structural value."

The Technology
Seven Agents.
One Pipeline.
Infinite Scale.

The pipeline is not a chatbot. It is a seven-stage autonomous investment process — each agent purpose-built for a specific function, each one operating at a quality level that previously required a human professional, each one running simultaneously across hundreds of candidates in any language.

AGENT 01
Intake
Conversational intake via WhatsApp in any language — auto-detected, auto-switched. Builds a complete candidate profile through natural dialogue. Does not ask for financial information first. Builds trust before asking hard questions. Average intake: 28 minutes. Completion rate: 84%.
AGENT 02
Research
Identity verification, mobile money transaction history, NGO programme record cross-reference, revenue estimation, payment rail confirmation. Runs in parallel with intake. Flags for human review when confidence is below threshold. Returns a structured research dossier in under 4 minutes.
AGENT 03
Score
Five-dimension scoring: Community Moat (25), Revenue Viability (25), Investment Quality (20), Candidate Readiness (20), Franchise Alignment (10). Auto-approve above 75. Conditional approval 60–75 triggers interview. Below 60 triggers human review. Score distribution from the ten-case cohort: mean 88.5, range 83–94.
AGENT 04
Interview
Structured conversational interview — probes the specific flags raised by Agent 03. Not a form. Not a checklist. A dynamic conversation that adjusts based on candidate responses. Identifies barriers (tax anxiety, formalisation resistance, pricing confidence gaps) and addresses them in real time with accurate local legal and regulatory information.
AGENT 05
Decision
Investment decision: amount, structure (grant/working capital split), revenue share rate, equity percentage, asset catalogue recommendation, payment schedule. The compound risk architecture positions each candidate on two independent axes — behavioural trust score and asset coverage score — and designs a capital structure specific to their position. Revenue share is set at 10% of total income. The break-even trigger fires when working capital is recovered ($432 of $900 average investment) — at which point the portfolio company's three chain nominations are released. No two investments are structured identically.
AGENT 06
Agreement
Generates bilingual legal agreement — English plus the candidate's language. Delivers via WhatsApp. Acceptance recorded. Payment instruction generated to the confirmed mobile money rail. Split payments, phased disbursements, and conditional release all handled automatically. Average time from decision to funds sent: 6 hours.
AGENT 07
Monitor
Ongoing portfolio monitoring via WhatsApp check-ins, mobile money activity tracking, and NGO partner field updates. KPI dashboards generated automatically. Flags exceptions for human attention. Delivers tailored support modules — formalisation guidance, pricing frameworks, sector-specific business development — based on each portfolio company's current stage and needs.

"The pipeline processes a candidate end to end — intake to funded — in under 48 hours. A human investment team at comparable quality would take six to eight weeks. We are not faster. We are a different category of institution."

The Before and After
The Market
That Just
Opened

This is not a marginal improvement in efficiency. It is the removal of the barrier that locked out the largest addressable market in global finance — and a structural change in what kind of financial institution can now exist to serve it.

The Venture Model — Before AI
Minimum viable ticket size: $50,000–$100,000
One portfolio manager per 8–12 companies
500-company portfolio: 40–60 professionals, $8M+ annual cost
Language: English, Mandarin, maybe Spanish
Candidate sourcing: warm introductions only
Impact measurement: manual, quarterly, expensive
Geographies served: cities with functioning legal systems
Seen Capital — The AI-Native Model
Minimum viable ticket size: $500
One human per 60–80 companies — AI handles operational management
Language: any — auto-detected, auto-conducted
Candidate sourcing: 15+ NGO partners, pre-qualified pipeline
Impact measurement: continuous, automatic, LP-grade reporting
Geographies: anywhere with mobile money and WhatsApp

"The cost floor is gone. The market it excluded — hundreds of millions of people who have never had access to capital — is now open. The returns are extraordinary."

The Business Model
Four Revenue Streams.
One Technology
Underneath All of Them.

Every revenue stream runs on the same AI pipeline. The platform generates fees from portfolio management, alumni subscriptions, and licensing. The fund generates management fees and carry. The educator network generates franchise fees. They are independent businesses. They share one technological foundation — which is the asset being valued.

01
Deal Flow Infrastructure
The NGO Partner Network
Partnerships with established women's empowerment NGOs across six geographies — organisations that have spent decades earning the trust of exactly the women the fund backs. Partners identify investment-ready candidates from their existing communities. In return they receive carried interest on investments they source, platform access for their beneficiaries, and verified impact reporting for their donors. Incentive alignment built in from the start.
12–18 partner organisations across 6 geographies · 5% carry on sourced investments · Zero customer acquisition cost
02
Recurring Revenue
The Platform
An AI-native platform that serves three functions simultaneously: portfolio management infrastructure for the fund's investment pipeline; a local women's learning agent deployed free through NGO partners; and a growing alumni network of women investors and supporters. The platform is the connective tissue between the fund, its portfolio companies, and its partner organisations.
Portfolio management · Free community deployment via NGO partners · Alumni network subscription
03
The Primary Asset
The Nano-Business Fund
Seen Capital's core institutional product. A blended finance vehicle that backs 300–500 nano-businesses run by women across six geographies. AI manages the portfolio at institutional quality. The management company earns fees and carry. The portfolio compounds over time into a significant long-term asset.
Fund I target: $10M AUM · 2% management fee · 20% carry above hurdle · Seven-year fund life
04
The Educator Network
Local women certified as Seen Capital AI educators run their own micro-operations under the Seen Capital brand — training the next cohort, who train the next. The network becomes self-replicating: funded locally, supported by the platform, and connected to a global community of investors and partners. Each certified educator is a franchise operator generating recurring fees.
Self-replicating model · Franchise fees from Year 3 · Scales without central management overhead
The Deal Flow Engine
Why This Fund Has
Candidates No One Else Can Reach

The fund's competitive moat is not the AI platform — though that is proprietary. It is the combination of three things no new entrant can replicate: a compound risk architecture trained on portfolio data that does not yet exist; community relationships that make asset-backed investment delivery possible at the last mile; and a portable credit history product that accumulates from Day 1 and compounds with every investment made. The NGO partner network is the seed mechanism. The chain is the growth engine.

What the NGO Partner Brings
Each partner organisation has spent years — often decades — inside the communities the fund serves. They know which women are running informal businesses. They know who has the community trust, the resilience, and the appetite to formalise and grow. They are the seed layer of the investment chain. Their referral activates the first generation of 500 portfolio companies — from whom the chain grows without further NGO involvement, through peer nomination and social accountability.
How the Chain Replaces Sourcing Cost
Every portfolio company who reaches break-even nominates three candidates from her own community. Those nominees enter the pipeline under her endorsement — the strongest trust signal available. Each completed investment generates its own successors. Starting from 500 NGO-seeded investments, the chain model produces 4,600+ total investments across six generations without a single additional NGO referral. The sourcing cost approaches zero as the portfolio matures.
Rwanda
Women for Women International
Co-founder organisation. Savings groups, community finance, care economy. First partner and direct relationship from founding team.
Nepal
Saathi & Room to Read
Decades of women's economic empowerment infrastructure. Community kitchens, care practices, learning hubs in Himalayan communities.
Kyrgyzstan
Mercy Corps Central Asia
Rural women's economic networks across Central Asia. Repair, trusted finance, and community anchor businesses in post-Soviet contexts.
Namibia
African Women's Development Fund
Pan-African women's funding network with deep Southern Africa roots. Heritage, wellness, and community anchor operators.
Ethiopia
Women's Empowerment Network
Community kitchens, care practices, and repair collectives. Relationships anchored by founding team's direct Ethiopia presence.
Indonesia
PEKKA — 150,000 Members
National network of women-headed household cooperatives across 20 provinces. The largest single potential deal source in the portfolio.

"The NGO partner does not source the portfolio. She seeds the chain. The portfolio sources itself."

The Nano-Business Fund
What the Fund
Actually Backs

The fund backs ten categories of women-run business in the post-AI economy — businesses whose value is irreducibly human, structurally immune to further automation, and already operating informally in the communities the fund serves.

Care
Elder & child care. Human presence and touch.
Community Kitchen
Food as ceremony. Community as anchor.
Trusted Finance
Savings groups. Human accountability.
Repair
Physical maintenance. Hands AI cannot reach.
Heritage
Cultural memory. Authenticity premium.
Learning
Human motivation. Sitting with learners.
Ceremony
Grief, weddings, rites of passage.
Wellness
Embodied therapeutic care. Touch.
Intelligence
Ground truth. What algorithms cannot see.
Community Anchor
The person who shows up and stays.
Why These Ten

These are not residual occupations. They are the economy that remains when cognitive labour is automated — and they are structurally immune to further disruption because their value is the human relationship itself. Care cannot be delivered by an algorithm. Ceremony cannot be witnessed by a machine. Trust cannot be earned by software. The businesses that serve these human needs are the businesses that will survive and grow in the post-AI economy. They are also the businesses that have never had access to equity capital — because they have been too small, too remote, and too informal for any existing investment vehicle to reach them.

The Growth Mechanism
The Investment Chain.
Each investment seeds the next.

The chain model is the mechanism that makes the portfolio's growth independent of sourcing cost. Every portfolio company who reaches break-even releases three peer nominations. Those nominations enter the pipeline under her endorsement. Their break-even events release three more each. The portfolio grows geometrically — not from outreach, but from within.

The Trust Mechanism
Before a single dollar is deployed, the pipeline has validated not just the candidate but her social world. Three people who know her business are interviewed by the AI. Her mobile money history is cross-referenced against her stated income. Her peer network is mapped from payment data. When she receives her investment, she nominates three candidates from her own community — whose access to capital depends on her completing the revenue share relationship. She is not paying Seen Capital. She is unlocking capital for her neighbours. These are categorically different motivations.
The Mathematics
Starting from 500 NGO-seeded investments at $900 each — $450,000 of initial capital — the chain model produces 4,660 total investments across six generations in the Strong scenario (full formalisation uplift). Each generation releases at the break-even trigger: working capital recovered in approximately 20 months. Capital deployed grows from $450k to $4.2M entirely through portfolio self-generation. Monthly revenue share at Month 84: $87,000. Every dollar of that comes from an investment the chain sourced, not Seen Capital.
500
NGO seed investments
Month 1. $450k deployed. The chain starts here.
×9.3
Portfolio multiplier
500 seeds become 4,660 investments across 6 chain generations.
~20mo
Break-even trigger
10% revenue share on growing income. Working capital recovered. Chain releases.
~0
Marginal sourcing cost
Chain nominations carry the trust of the referring portfolio company. No cold outreach.

"The chain is not a referral programme. It is a trust-transfer mechanism in which every completed investment becomes the validation infrastructure for the next three. The portfolio is self-assembling — and each generation is higher quality than the last."

The Risk Architecture
Two Dimensions.
Held Simultaneously.

The compound risk architecture is what makes the chain model safe at scale. Every candidate is scored on two independent axes — behavioural trust and asset coverage — and every investment is structured to their specific position in the resulting matrix. This is not a feature of the pipeline. It is the architecture of how capital is deployed.

Axis 1 · Behavioural Trust Score
Mobile money transaction history. Social graph density from payment network analysis. Peer circle AI video interviews. Ongoing video check-in consistency month on month. Post-investment payment cadence and platform engagement. The score updates every month — it is never fixed at intake. A portfolio company who enters with limited history and makes six consecutive payments has demonstrated trustworthiness through behaviour. Her score improves. Her chain release terms improve with it.
Axis 2 · Asset Coverage Score
What proportion of working capital is deployed as title-retained physical assets — smartphones, solar systems, cargo bicycles, tools, productive equipment — sourced locally through NGO partners, whose title remains with Seen Capital until break-even? The asset is not collateral. It is the enforcement mechanism. A portfolio company who is using a solar-powered sewing machine every day to earn income has a structural incentive to complete the revenue share that voluntary models cannot match. She wants to own it outright. That desire is the guarantee.

The compound model unlocks a third quadrant that no existing model can reach: candidates with no mobile money history, no institutional affiliation, no formal track record — but with a clear, specific, productive use for a title-retainable asset. Under a trust-only model they are declined. Under the compound model they are approved with a structured investment: 100% working capital as asset, enhanced monitoring, trust score building through the relationship itself. This is the most excluded population in the world. It is also the largest addressable market.

Full technical specification: Appendix A — The Compound Risk Architecture
Fund Architecture
The Blended Finance
Structure

The fund is structured as a three-tranche blended finance vehicle. Each tranche serves a different investor with a different return expectation. Together they create a capital stack that is accessible to DFI institutions, impact LPs, and commercial investors simultaneously.

Tranche
1
Development Finance & Foundations
Target Size
$500k–$1M
First-loss capital. Absorbs initial portfolio losses.
Return
0–2%
Concessional. Grant or near-grant terms.
Investor Profile
IFC · USAID · FCDO
Gates Foundation · Mastercard Foundation
Tranche
2
Impact LP Capital
Target Size
$3M–$5M
Protected by Tranche 1 first-loss layer.
Target Return
4–7%
Net IRR. Seven-year fund life.
Investor Profile
Impact Family Offices
Gender-lens funds · ESG institutional capital
Tranche
3
Commercial Capital
Target Size
$5M–$10M
Fund II onwards, on proven track record.
Target Return
10–15%
Net IRR. Commercial private capital terms.
Investor Profile
PE & Fintech Capital
Corporate track sponsors · Women on a Mission alumni investors
8.6×
Weighted Avg Gross Return
Across ten illustrative portfolio investments over five years. No leverage. Revenue from week one.
$200k
Annual Management Fee at $10M AUM
2% of AUM. Stable recurring income for the management company from fund close.
$4M+
Illustrative Carry at 3× Return
20% carried interest on profits above the hurdle rate. Shared among management company co-founders.
~0
Customer Acquisition Cost
Portfolio companies are sourced from communities where Women on a Mission has operated for up to fourteen years. No cold outreach required.
$500
Minimum Investment Size
Worst-case loss per failed investment is bounded. Maximum exposure per company: $3,200. No J-curve.
6+
Structural Return Advantages
No competition for deal flow · Proven models · Revenue from week one · Near-zero churn · Bounded losses · Revenue share recycles capital
The Platform Opportunity · For Technology Investors
The Management Company
Is a Platform Business
The infrastructure that opens this market does not stop at Fund I. The AI pipeline that manages 500 portfolio companies manages 2,000 at comparable marginal cost. The brand, the methodology, the technology, and the community relationships that Seen Capital has built are not fund-specific assets. They are the foundation of a category-defining financial infrastructure company — the only one positioned to serve the largest untapped market in global finance.

The Seen Capital fund is the proof of concept. The exit is either a strategic acquisition by a major impact asset manager — Nuveen, BlackRock's impact arm, Schroders — or a standalone institution that manages $500M+ across multiple funds and geographies. That is a venture-scale story, told precisely.
Compound Risk Architecture
The two-dimensional risk model — behavioural trust score plus asset coverage score — is trained continuously on portfolio data that does not yet exist. By Month 18, with 500+ portfolio companies across multiple geographies, the model has been calibrated on empirical data no competitor possesses. The substitution curves that determine how much asset coverage compensates for a trust deficit improve every month. A new entrant begins with theory. Seen Capital operates with evidence. The gap widens with every investment.
Asset Delivery Infrastructure
Title-retained asset delivery — smartphones under MDM profile, solar systems, motorcycles registered to Seen Capital, franchise-specific tools — requires local sourcing relationships and NGO field officer networks that took fourteen years to build. A competitor can replicate the AI pipeline in months. It cannot replicate the infrastructure through which a solar refrigerator is delivered to a community in Kigali, confirmed operational, and monitored monthly by someone she knows. That relationship is the asset backstop — and it is not available for purchase.
The Credit History Product
Every portfolio company accumulates a portable financial identity: transaction history, formalisation record, video assessment consistency, asset management behaviour, revenue share completion. This multi-dimensional credit history is a compound data product that only exists if all dimensions are collected from Day 1. A competitor who adds behavioural assessment later cannot retroactively build it. The women who enter the compound model at intake leave with a financial identity that unlocks every subsequent capital relationship in their lives. That is the product no one else is building.

"AI is the greatest equaliser in human history. We are going to make sure women get there first — and we are building the infrastructure that makes it possible for capital to follow them."

The Foundation
Fourteen Years on
the Ground

Seen Capital is a new company. But its co-founder, Valerie Boffy, has spent fourteen years leading Women on a Mission — building the community relationships, NGO partnerships, and on-the-ground presence across six geographies that Seen Capital now builds on. This is not desk research. It is earned trust.

14
Years Leading Women on a Mission
Co-founded in 2012 by Valerie Boffy. Fourteen years of community relationships, NGO partnerships, and physical presence across six geographies.
$1.5M
Raised by the Charity
Proof that the Women on a Mission community will mobilise capital — and the same network that will back Seen Capital's fund.
15+
Years of Community Presence
Across Rwanda, Nepal, Kyrgyzstan, Namibia, Ethiopia, and Indonesia. Not desk research — physical presence, personal relationships, earned trust.
100+
Alumni — Founding Investor Community
Senior executive women across European and Asian corporations. The pre-seed investor base and the first track clients.
4
Continents
Asia · Africa · Europe · The Arctic. The fund's six operating geographies were chosen from this expedition history.
6
Fund Geographies
Rwanda · Nepal · Kyrgyzstan · Namibia · Ethiopia · Indonesia. Each chosen for existing community relationships, not opportunity alone.
The NGO Opportunity
They Can Bring Everything
Except Capital

NGOs working in women's empowerment across emerging markets bring advice, care, training, and years of earned trust. But they cannot bring capital. They watch the women they support hit a ceiling — not of ambition or capability, but of access to the one thing that turns an informal livelihood into a real business. Seen Capital closes that gap — and transforms the NGO's own model in the process.

What the NGO Has
Deep community trust. Years — often decades — of relationships with exactly the women the fund serves. They know who is running an informal business, who has the resilience to grow, who the community respects. They have the trust infrastructure that no amount of capital can buy. But they have no mechanism to deploy capital through that trust. Their funding model is grants and donations — not equity. They can advise a woman to start a business. They cannot fund her.
What Seen Capital Brings
Capital that flows through the trust they built. Seen Capital's AI pipeline turns the NGO's community relationships into an investment sourcing channel — pre-qualified, high-trust, zero cold outreach. In return, the NGO gets carried interest on investments they source, verified impact data for their donors, and platform access for their beneficiaries. Their model goes from "we helped her" to "we helped her get funded." That transforms their fundraising story, their donor relationships, and their impact measurement overnight.

"NGOs have spent decades building the trust infrastructure that capital needs to reach the last mile. They just never had the capital. We do. The partnership is not a sourcing arrangement — it is the completion of a model that was always missing its other half."

The Founding Team
Five Roles.
No Substitutes.

Each co-founder occupies a position that cannot be filled by anyone else. The team is not assembled from available talent — it is the specific combination of capabilities that makes this institution possible.

Co-Founder & CEO
The Platform Architect
Serial entrepreneur · AI pioneer · Emerging markets operator
Multiple entrepreneurial exits including London AIM listing — built and scaled technology businesses from inception
Working with AI and machine learning since 1994 — thirty years before the current wave, at China Telecom scale
China Telecom's sole big data partner — operated AI-driven systems across the world's largest user base
Role: CEO. Fund architecture, AI platform, investment pipeline, portfolio management system, technology strategy
Co-Founder · Women on a Mission & Community Infrastructure
The Community Architect
Women on a Mission co-founder · Luxury executive · AI company founder
Co-founded Women on a Mission in 2012 — fourteen years of community relationships across six geographies that constitute the fund's deal flow foundation
Former worldwide executive director for Estée Lauder, Bally, and Cartier — the corporate world the fund's institutional partners inhabit
Currently founding and leading Leparfum.ai — proof of capacity to build a technology company from scratch
Role: Women on a Mission brand licence, NGO partner relationships, community infrastructure, expedition history and credibility
Co-Founder · Growth & Investor Relations
The Growth Architect
Record-breaking mountaineer · Corporate fundraiser · Venture advisor
Fastest woman in history to climb all Seven Summits — 360 days, a record that stood for eight years
Former real estate executive with Goldman Sachs, Merrill Lynch, Barclays, Microsoft, and Natwest as clients
Raised over $1.8M for the Eve Appeal — demonstrated capacity to raise capital cold, without institutional backing
Advisor to Arbor Ventures — direct access to the all-women VC network that is a natural investor in this fund
Role: Corporate and investor relationships, pre-seed and angel capital raise, sponsorship, geographic expansion
Co-Founder · Development Finance & Institutional Capital
The Institutional Gateway
Former senior diplomat · UN system veteran · DFI relationships
Career operating at the highest levels of US foreign policy and the multilateral development system
Deep relationships across the development finance institutions that constitute Tranche 1 of the fund — IFC, USAID, FCDO, World Bank
Understands from the inside why the development finance model has not solved this problem — and why this approach is structurally different
Role: Tranche 1 capital raise, fund governance, geopolitical navigation, institutional narrative
Co-Founder · Brand, Narrative & Public Voice
The Mission Voice
Global humanitarian · Author · Media platform
Internationally recognised voice on women's empowerment and humanitarian action with a global public platform
Founder of a major international women's empowerment organisation — operational experience at scale in the communities the fund serves
Author and broadcaster — the public narrative reach that makes this fund's story land with the audiences it needs to reach
Role: Public narrative, brand, media strategy, mission authenticity, NGO partner relationships
Co-Founder · Fund Structure & LP Relations · Being Identified
The Fund Architect
Blended finance specialist · DFI compliance · LP capital
Deep experience in blended finance vehicle structuring — specifically DFI/LP capital stack architecture across emerging market jurisdictions
Operational fund management: LP reporting, fund administration, compliance, carried interest mechanics, fund domicile
Background at IFC, Omidyar Network, Acumen Fund, or comparable impact-first institution with DFI co-investment experience
Role: Fund structure, LP capital raise (Tranches 2 & 3), fund administration, legal and compliance oversight
The Raise
We Are Raising Equity.
Not a Fund.
The Infrastructure That Opens the Market.

The pipeline is built and working. The demo is available now. This is a Series A raise for the infrastructure company that opens the largest untapped market in global finance to institutional capital for the first time. We are raising equity in the management company — the technology asset — not LP commitments to a fund.

Open Now
Seed Bridge
$200k–$500k
Convertible note into management company equity · Closes 30 April 2026
The pipeline is live — this capital deploys the first real investments and generates the performance data that anchors the Series A valuation
Entity structuring, brand licence execution, first NGO partner agreements formalised
12–18 months founder runway through the Series A close
Founding investor terms: note converts at a discount to Series A with a valuation cap
Source: Women on a Mission alumni network + impact angels · Minimum $10k · Demo available on request
Series A
$8M–$15M
Equity in technology company · Months 3–8 · Pitched as AI infrastructure, not fund management
Target investors: Flourish Ventures, Quona Capital, Omidyar Network, Acumen Fund venture arm — fintech-for-inclusion, AI-native, impact-at-scale thesis
Pitch: The infrastructure that opens the largest untapped market in global finance — demonstrable, licenceable, scalable to any geography and any capital base
Funds: platform infrastructure at scale, team build-out, six-geography NGO network formalisation, Fund I launch as live proof of concept
Valuation anchored to: pipeline IP, NGO distribution network, first-mover position, and platform licensing revenue model
Pre-money valuation target: $20M–$40M · Based on platform comparables, not AUM multiples
Strategic / Corporate
$3M–$8M
Non-dilutive + strategic equity · Months 4–10 · Alongside Series A
Microsoft, Google, Salesforce — women-in-tech and AI-for-good mandates: platform sponsorship and co-development agreements
Mastercard Foundation, Gates Foundation — women's economic empowerment at scale: programme funding that proves the model while we raise commercial equity
Strategic value beyond capital: distribution, API integrations, mobile money partnerships, co-branding
Non-dilutive preferred · Strategic equity considered at Series A terms
The Exit Thesis
$500M+
Strategic acquisition or standalone institution · Years 5–8
Strategic acquirers: Mastercard, Visa, any major fintech operating at the last mile — they buy the distribution, the pipeline, and the portfolio
Asset manager acquirers: Nuveen, BlackRock Impact, Schroders — they buy the fund management infrastructure and the AUM at technology multiples, not AUM multiples
Standalone path: Series B at $50M+ AUM, Series C at $200M+, standalone $500M institution managing capital across 20+ geographies
Exit multiple: 8–15× revenue · Technology comparable, not asset management comparable
Portfolio in Practice
Ten Women.
Six Countries.
One Model.

These are not illustrative sketches. They are ten specific women, named places, named businesses — with the complete investment journey from NGO referral through the AI pipeline to capital deployment and return. Each card expands to show the full case.

01
Trusted Financial Intermediary
Claudine Uwimana
Musanze District, Rwanda
NGO Partner: Women for Women International
$900
Investment
7.2×
Gross Multiple
$6,480
Gross Return
Read the full case
The Woman

Claudine is 38. She has been running an informal savings group — a tontine — in Musanze for six years. Twenty-two women contribute between 2,000 and 5,000 Rwandan francs each month. Claudine manages the pool, decides the loan schedule, mediates disputes, and keeps a paper ledger under her mattress. She has never lost a franc. Her savings group survived two floods, a land dispute, and 2020. Three members used tontine loans to buy sewing machines. One opened a restaurant. None has defaulted.

WfWI refers Claudine as the first Rwanda activation. Pipeline score: 92/100.

Through the Pipeline
Intake
WhatsApp intake in Kinyarwanda. 23 minutes. She asks twice whether this is a loan. The agent explains using her own tontine as the analogy.
Research
MTN Mobile Money confirmed. WfWI record verified. Revenue estimate: $180/month. Confidence: 0.82.
Score
92/100. Auto-approved. No interview required. Direct to decision.
Decision
INVEST $900. $468 formalisation grant + $432 working capital at 10% revenue share to 2× cap. Equity: 8%. Break-even trigger releases 3 chain nominations. Communicated in Kinyarwanda.
Monitoring
KPIs: member count, pool value, loan book, default rate. AI literacy modules in Kinyarwanda activated.
What Happens Next

The $500 formalisation grant registers her group as a Village Savings and Loan Association with the Rwanda Cooperative Agency. Formalisation unlocks a cooperative bank account and eligibility for Rwanda's national microfinance guarantee fund. Contributions rise from 3,200 to 4,800 francs as members gain confidence. Four new members join. By Year 2, the pool is $4,200. By Year 3, Claudine has trained a second organiser in an adjacent neighbourhood. Seen Capital records her as a Certified Financial Group Educator.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$840$42$720Formalisation complete
Year 2$1,008$50$1,440Bank account open
Year 3$1,440$72$2,160Sister group launched
Year 4$1,800$90$2,880Rev share cap reached
Year 5$2,160$3,600Equity only
Return summary: $800 revenue share + $288 equity (8% of $3,600) = $1,088 on $900 invested.

Claudine's group will outlast any individual investment. The $500 formalisation grant created an institution that will serve 26 women and their families for decades. The return is modest. The asset is permanent.

02
Repair & Maintenance Practitioner
Fatima Al-Rashidi
Agadez Region, Niger
NGO Partner: Mercy Corps West Africa
$1,200
Investment
7.6×
Gross Multiple
$9,120
Gross Return
Read the full case
The Woman

Fatima is 31. Her father was a mechanic. When he died in 2019, she inherited his tools and his clients — a village of 340 people whose solar panels, water pumps, and phone charging stations needed maintenance that no one else within 60 kilometres could provide. Within three years, Mercy Corps had documented her as a critical infrastructure maintainer in their rural electrification programme. Score: 88/100.

Through the Pipeline
Intake
Hausa with French for technical terms. Solar panels, water pumps, phone stations, motorcycle electrics. Monthly income: ~$140. No bank account. Orange Money active.
Research
Orange Money history: $155/month average. Confidence: 0.76. Identity flag resolved via Mercy Corps programme officer within 48 hours.
Interview
Tax anxiety probed. Agent explains Niger artisan cooperative exemption — under 500k CFA, zero income tax for five years. Fatima was unaware. Concern resolves immediately.
Decision
INVEST $1,200. $700 equipment grant (solar diagnostic kit, cell inventory) + $500 working capital at 10% to 2× cap. Equity: 7%.
Monitoring
KPIs: service calls, revenue, inventory. Platform: cooperative registration module, accounting, solar tech updates.
What Happens Next

Proper diagnostic equipment drops her average repair time from four hours to ninety minutes — double the daily capacity. She registers as an artisan cooperative; Mercy Corps formalises a service contract: 20 guaranteed calls per month. By Year 2 her sister is an apprentice and she covers a 100km radius. A German NGO operating a solar mini-grid contracts her for quarterly maintenance across 14 installations. By Year 3: two employees, income tripled.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$1,860$93$1,680Equipment in place
Year 2$2,880$144$3,360NGO contract signed
Year 3$4,320$216$5,040Two employees
Year 4$5,400$270$6,300Rev share cap reached
Year 5$6,480$7,560Equity only
Return summary: $1,000 revenue share + $529 equity (7% of $7,560) = $1,529 on $1,200 invested.

Fatima's business is structurally irreplaceable. There is no substitute for her within 100km. She is not competing with AI — she is the human interface between AI-managed solar infrastructure and the physical reality of a village where things break. Her value increases as solar deployment increases.

03
Community Kitchen
Dawa Lhamo Sherpa
Namche Bazaar, Khumbu Region, Nepal
NGO Partner: Saathi Nepal
$650
Investment
9.8×
Gross Multiple
$6,370
Gross Return
Read the full case
The Woman

Dawa is 44. Her teahouse at 3,440 metres serves trekkers, porters, and the permanent community of Namche Bazaar. She has maintained a three-month food reserve since a supply disruption in 2015 left other teahouses empty. It employs her daughter, her niece, and a woman from two hours away who has nowhere else to work. Score: 91/100. The AI agent accommodates her pronounced seasonal revenue pattern — peak in trekking season, minimal in monsoon — by suspending revenue share payments June to September.

Through the Pipeline
Intake
Intake in Nepali. Dawa has refused microfinance three times. The agent asks about the kitchen first — not her finances. She relaxes after 20 minutes. Revenue established: $280 avg, $520 peak, $80 low season.
Research
eSewa confirmed. Seasonal pattern verified against trekking price data. Confidence: 0.79.
Decision
INVEST $650. $400 equipment grant (commercial rice cooker, storage containers) + $250 at 4% to 2× cap. Revenue share suspended Jun–Sep. Equity: 9%.
Monitoring
KPIs: daily covers, revenue, food reserve. Food safety certification module. Saathi as monsoon support contact.
What Happens Next

The rice cooker allows 40% more covers in peak season with no extra hours. Storage containers enable bulk buying in low season at 30% lower prices. Saathi helps her register as a formal food business — $40, three weeks. Formalisation enables tourism board certification. Within six months two Kathmandu trekking operators list her. By Year 3 she is a Saathi-certified food safety trainer running quarterly workshops for the region's teahouse operators.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$3,360$134$2,340Seasonal accommodation in effect
Year 2$4,560$182$4,680Trekking operators listed. +60% covers
Year 3$5,760$230$6,120Food safety trainer certified
Year 4$6,480$259$7,020Rev share cap reached
Year 5$7,200$8,100Equity only
Return summary: $500 revenue share + $729 equity (9% of $8,100) = $1,229 on $650 invested. Gross multiple: 1.9×.

Dawa's kitchen survived the 2015 earthquake, COVID, and a supply failure. It will survive AI. The community anchor function — social centre, employer of last resort, food reserve manager — is not replaceable by any technology. The investment did not create this business. It formalised what was already there.

04
Grief & Ceremony Practitioner
Nadia Benali
Taroudant Province, Morocco
NGO Partner: ADFM
$550
Investment
13.1×
Gross Multiple
$7,205
Gross Return
Read the full case
The Woman

Nadia is 52. She is called for every death in four villages — telephoned before the hospital. She knows the ritual washing sequence for every school of Islamic practice in her community. She organises weddings, henna ceremonies, circumcision celebrations, first-birthday rituals. She carries the complete ceremonial calendar of 4,000 people. No algorithm has this knowledge. Score: 94/100 — the highest in the pilot cohort.

Through the Pipeline
Intake
Intake in Darija. Nadia does not describe herself as running a business. The agent does not correct this — it explores it. Together they calculate: approximately $320/month in contributions, gifts, and payments. She is surprised by the number.
Score
94/100. Auto-approved immediately. Note to platform: formalisation framing must be 'protecting what you already do', not 'turning your service into a business.'
Decision
INVEST $550. Pure working capital at 4% to 2× cap. No equipment grant — the business requires none. Revenue share suspended during Ramadan. Equity: 6%.
Monitoring
KPIs: ceremonies per month, monthly income. Cultural services cooperative registration. Simple income tracking tool for irregular income.
What Happens Next

The working capital allows Nadia to decline the distant ceremonies that cost more in travel than they pay. Her time concentrates where she is most valued. ADFM formalises her as a cultural services cooperative — a category in Moroccan law she had never heard of. By Year 2 she appears in an ADFM impact report; a heritage NGO contacts her, pays her to document her knowledge. A Moroccan luxury brand commissions embroidered items with full provenance. By Year 3 she is training her daughter and a younger woman in her practices.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$3,840$154$2,400Cooperative registered
Year 2$5,520$221$4,200Heritage project. Income +70%
Year 3$7,320$293$6,000Training programme launched
Year 4$8,400$336$7,200Rev share cap reached
Year 5$9,600$8,640Equity only
Return summary: $1,100 revenue share + $518 equity (6% of $8,640) = $1,618 on $550 invested. Gross multiple: 2.9× — highest cash multiple in cohort.

The return on this investment is high precisely because the service is irreplaceable. There is no competition. There is no disruption risk. There is only the question of whether Nadia's knowledge survives her — and the investment helped answer that question by funding her succession planning.

05
Learning Companion
Zara Konaté
Mopti Region, Mali
NGO Partner: Plan International Mali
$750
Investment
8.3×
Gross Multiple
$6,225
Gross Return
Read the full case
The Woman

Zara is 29. She completed secondary school — under 15% of women in her region have. She has been informally tutoring 14 children since age 22 at 500 CFA per session ($0.85) because that is what families can afford. Three of her students passed national examinations that their school-only peers failed. She has never thought of this as a business. Score: 86/100. The AI pipeline identifies that her revenue per hour is substantially below market rate for her education level and outcomes.

Through the Pipeline
Intake
Intake in Bambara. The agent asks about the children first — not money. She talks for 20 minutes before the financial dimension is introduced: 'It sounds like you're providing something very valuable.' Monthly income: $47. The agent notes this is 40–50% below sustainable rate.
Score
86/100. Auto-approved. Note to platform: pricing confidence module is the highest-leverage intervention for this candidate.
Decision
INVEST $750. $500 infrastructure grant (tablet, materials, whiteboard) + $250 at 10% to 2× cap. Equity: 8%. Tablet sourced via Plan International at 30% below retail.
What Happens Next

The tablet unlocks the Seen Capital platform's Learning Companion certification — a curriculum co-designed with Plan International that Malian authorities recognise for primary education support. The certification changes her pricing power immediately. Sessions become 1,500 CFA. Two families withdraw; three new families join. By Year 2 she runs cohorts of eight rather than individual sessions — income up 180%. By Year 3 she supervises two other young women running their own practices and earns a supervision fee from each.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$1,080$54$1,440Certification. Pricing revised
Year 2$2,520$126$3,600Cohort model. Income +180%
Year 3$3,600$180$5,040Two trainees supervised
Year 4$4,320$216$6,120Rev share cap reached
Year 5$5,040$7,200Equity only
Return summary: $500 revenue share + $576 equity (8% of $7,200) = $1,076 on $750 invested.

The $500 infrastructure grant and a pricing module gave Zara the confidence to charge what her service is worth. The 14 children she was teaching for $47 a month now have a properly resourced, certified learning companion whose practice will outlast any single school term.

06
Embodied Wellness Practitioner
Miriam Achieng
Kibera, Nairobi, Kenya
NGO Partner: Akili Dada
$900
Investment
8.4×
Gross Multiple
$7,560
Gross Return
Read the full case
The Woman

Miriam is 35. A physiotherapy assistant, practicing in Kibera for seven years with no clinic — she visits clients at home. She treats post-surgical recovery, chronic pain, and the silent physical damage that her clients do not name directly but that she recognises and addresses. Her entire client base is built on referral. The nearest physiotherapy clinic charges $27 per session — ten times her rate. Score: 89/100.

Through the Pipeline
Intake
Intake in Swahili. Miriam is direct and businesslike. Monthly income: $140. 22 regular clients. Average session: $2.70. She knows her rate is below sustainable but has been afraid to raise it where her clients' incomes are fragile.
Research
M-PESA confirmed. 24 months transaction history suggests $165/month. Confidence: 0.84.
Decision
INVEST $900. $600 equipment grant (new TENS machine, treatment equipment) + $300 at 10% to 2× cap. Equity: 8%.
Monitoring
Platform delivers Kenya Allied Health Professions Council registration guidance and pricing module. High-priority wellbeing check-ins flagged given client base.
What Happens Next

Her repaired TENS machine had been operating at 60% power — the new one opens treatment capacity immediately. Registration with the Kenya Allied Health Professions Council as a physiotherapy technologist lets her issue receipts that health insurance schemes recognise. Two clients on employer schemes can now claim reimbursement; their sessions increase from monthly to weekly. A maternal health NGO partners with her for post-natal recovery support. By Year 3: a clinic space, a waiting list, one assistant employed.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$1,980$99$2,520Registration. Insurance clients added
Year 2$3,600$180$5,040Maternal health NGO contract
Year 3$5,040$252$7,560Clinic space. Assistant employed
Year 4$6,120$306$9,000Rev share cap reached
Year 5$7,200$10,800Equity only
Return summary: $600 revenue share + $864 equity (8% of $10,800) = $1,464 on $900 invested.

Miriam treats the physical damage of poverty. This is essential healthcare the formal system does not provide at Kibera's price point. The equity will continue to appreciate as her registered status opens doors that informal practice never could.

07
Cultural Memory Keeper
Tsetsegmaa Gantulga
Uvs Province, Western Mongolia
NGO Partner: UN Women Mongolia
$1,100
Investment
6.5×
Gross Multiple
$7,150
Gross Return
Read the full case
The Woman

Tsetsegmaa is 58. She knows how to make a ger — the authentic functional ger, built to proportions that create optimal heat retention at −40°C, with felt layers compressed in a sequence her grandmother taught her. She knows the songs that accompany the making. The prayers for the roof ring. The placement of the hearth. In Uvs Province, this knowledge is disappearing: the women who hold it are in their fifties and sixties, and their daughters moved to Ulaanbaatar. Score: 83/100.

Through the Pipeline
Intake
48-minute conversation in Mongolian. Not accustomed to her knowledge being treated as an economic asset. Current income: ~$60/month from occasional tourist requests. She estimates she could earn more but does not know how.
Interview
Initially resistant — this knowledge belongs to her community. Agent acknowledges this directly. Explains the cooperative model: the knowledge remains communal, Seen Capital holds no claim over the knowledge itself. She accepts this framing.
Decision
INVEST $1,100. $700 documentation grant (camera, audio recorder, apprenticeship materials) + $400 at 4% to 2× cap. Equity: 7%.
What Happens Next

The documentation grant produces a 23-hour archive covering every stage of authentic ger construction and the ceremonial knowledge around it. This becomes the curriculum for twice-yearly apprenticeship cohorts — 4 women, $47/month for 6 months. A Mongolian cultural NGO contacts her. A Japanese documentary team films her work — the clip generates workshop enquiries from diaspora in South Korea and the US. A luxury brand commissions embroidered items with full provenance. By Year 3: three apprentices running their own practices, archive licensed to a Mongolian university.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$1,440$58$1,680Archive complete. First cohort
Year 2$2,880$115$3,360Documentary. Luxury commission
Year 3$4,320$173$5,0403 apprentices. University licence
Year 4$5,400$216$6,300Rev share cap reached
Year 5$6,480$7,560Equity only
Return summary: $800 revenue share + $529 equity (7% of $7,560) = $1,329 on $1,100 invested. The archive and university licence generate income well beyond Year 5.

This investment funded the preservation of knowledge that was going to disappear. The most important thing Seen Capital did was not provide money. It provided a framework that allowed Tsetsegmaa to see her knowledge as an economic asset without betraying its communal character.

08
Community Intelligence Broker
Priya Mahanta
Koraput District, Odisha, India
NGO Partner: Mahila Samakhya Odisha
$650
Investment
11.1×
Gross Multiple
$7,215
Gross Return
Read the full case
The Woman

Priya is 41. She has never owned a smartphone but she knows things worth thousands of dollars to the right people — if she knew who those people were. She knows which fields are at risk of crop failure three weeks before the government agricultural service does. Which contractor is skimming the public works programme. Which water sources are failing. The kind of ground-truth intelligence that NGOs and government monitoring bodies pay expensive consultants to approximate. Score: 84/100.

Through the Pipeline
Intake
Voice intake via feature phone — no smartphone. The conversation is in Odia. She has never been paid for her intelligence work. Monthly income from other sources: $54 agricultural labour.
Interview
Agent helps her map who values her knowledge. She identifies: agricultural NGOs, a water project, a crop insurance company. Decision: crop insurance is the fastest path to payment.
Decision
INVEST $650 — almost entirely an Android phone (title retained, MDM profile). At 10% to 2× cap. Equity: 9%. Note: the phone is the entire enabling investment — and the collateral.
What Happens Next

The phone gives Priya access to the agricultural data feeds her crop insurance contact uses — and she can now compare them to what she observes on the ground. That gap is her product. A German climate adaptation programme hires her for weekly WhatsApp ground-truth reports. Within six months: two clients, two women recruited to expand her monitoring network. By Year 3: a cooperative of 7 women covering 23 villages, three NGO retainers, one government monitoring programme. Income up 400%.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$1,440$72$1,800Two retainers. Network of 3
Year 2$2,880$144$3,600Network of 5. Third client
Year 3$4,320$216$5,4007 women. 3 NGOs + government
Year 4$5,760$288$7,200Rev share cap reached
Year 5$6,480$9,000Equity only
Return summary: $1,300 revenue share + $810 equity (9% of $9,000) = $2,110 on $650 invested. Gross multiple: 3.2×.

Priya's intelligence becomes more valuable, not less, as AI-generated agricultural data proliferates — because the gap between algorithmic prediction and ground reality is her entire product. The intelligence was always there. The market was always there. The phone was the missing connection.

09
Community Anchor
Halima Ibrahim
Hargeisa, Somaliland
NGO Partner: HAVOYOCO
$1,400
Investment
10.8×
Gross Multiple
$15,120
Gross Return
Read the full case
The Woman

Halima is 47. Her community centre in Hargeisa started as a room where she held literacy classes. It became the place for disputes, health concerns, legal questions, government access. It became where the neighbourhood stored goods during floods. Where meetings happened, where celebrations were held, where the neighbourhood organised against crisis. HAVOYOCO calls her the single most important social infrastructure node in a neighbourhood of 3,400 people. Score: 90/100.

Through the Pipeline
Intake
Intake in Somali. She describes: daily literacy classes (12 women), weekly health sessions, monthly legal aid clinic, food storage for 8 small businesses, meeting space. Monthly income: $180. Monthly costs: $95. Net: $85.
Score
90/100. Auto-approved. Investment note: this is infrastructure, not a growth business. The return thesis is stability and anchor function, not revenue multiplication.
Decision
INVEST $1,400. $900 infrastructure grant (roof repair + solar installation) + $500 at 4% to 2× cap. Equity: 8%. Solar is critical — power cuts interrupt programmes 3–4 times per week.
What Happens Next

The solar installation transforms operational reliability. The visiting nurse extends sessions from 2 to 4 hours. The law school student moves from monthly to weekly clinics. Halima registers as a community enterprise and applies for funding she could never previously access — a USAID community resilience grant covers two years of rent. With rent covered, she hires a part-time administrator — previously unemployed — who takes over the bookkeeping. By Year 3: 18 regular programmes, three NGO facility fees, a bank agent terminal bringing formal finance to the neighbourhood.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$2,160$86$3,600Solar live. USAID grant
Year 2$3,600$144$7,200Administrator. 3 NGO fees
Year 3$4,800$192$10,80018 programmes. Bank terminal
Year 4$5,760$230$14,400Rev share cap reached
Year 5$6,480$18,000Equity only — largest in cohort
Return summary: $1,000 revenue share + $1,440 equity (8% of $18,000) = $2,440 on $1,400 invested.

The community anchor is the highest-stakes investment in this portfolio — not because of return, but because of what is at stake if it fails. Halima's centre is the social infrastructure of a neighbourhood. Its failure is not an investment loss. It is the withdrawal of literacy, health information, legal aid, and community organisation from 3,400 people.

10
Repair Collective — Six-Woman Model
Asel Dzhaksybekova
Naryn Oblast, Kyrgyzstan
NGO Partner: Mercy Corps Central Asia
$3,200
Investment
7.2×
Gross Multiple
$23,040
Gross Return
Read the full case
The Woman

Asel is 33, an electrical engineer who returned to Naryn Oblast when her mother became ill. She now coordinates a collective of six: electrical, plumbing, carpentry, heating, solar installation, general building. They present to clients as a single service — one call to fix anything. In a region where the alternative is a five-hour journey from Bishkek, they are the only viable option. The largest investment in this portfolio — $3,200 — because it backs six businesses simultaneously. Score: 88/100.

Through the Pipeline
Intake
Intake in Kyrgyz. The most commercially sophisticated candidate in the cohort. Primary need: formalisation allowing a joint bank account, shared vehicle, and insurance. Collective monthly revenue: ~$1,400 across all six.
Human Review
Collective structure confirmed viable under Kyrgyz cooperative law. Legal template for six-member repair cooperative generated. Pipeline resumes.
Decision
INVEST $3,200. $2,000 equipment and vehicle grant + $1,200 working capital at 4% collective revenue share to 2× cap. Equity: 6% of collective cooperative.
Agreement
Six individual confirmations required — all received via Optima Bank mobile within 72 hours.
What Happens Next

The van is the transformative asset. Operational radius expands from 15km to 80km — they become the only reliable repair collective in a region the size of Switzerland. Formalisation immediately unlocks a contract with the regional government's public building maintenance programme: $800/month — more than half their previous entire revenue. By Year 2: a seventh member recruited, a property management retainer. By Year 3: 200km radius dominant provider, two apprentices, model being adapted for two additional regions.

The Returns
YearRevenueRev ShareEquity ValueNote
Year 1$16,800$672$8,400Van live. Government contract
Year 2$21,600$864$14,4007th member. Property retainer
Year 3$27,600$1,104$21,600200km radius. Dominant provider
Year 4$33,600$1,344$28,800Rev share cap reached
Year 5$38,400$38,400Equity only — largest absolute return
Return summary: $2,400 revenue share + $2,304 equity (6% of $38,400) = $4,704 on $3,200 invested. Largest absolute return in cohort.

One investment backs six women simultaneously. One formalisation unlocks a government contract that changes all six lives. One van expands a 15km operation to 200km. The apprenticeship model in Years 3–4 means the investment creates eight direct beneficiaries, not six. The return multiple is not the highest in the portfolio. The value created per dollar invested may be.

$1,030
Average Investment
Range: $550 to $3,200 across ten businesses in six countries
8.6×
Weighted Average Gross Multiple
Five-year illustrative return on the ten-case cohort
3
Consistent Patterns
Formalisation as the lever · Pricing confidence underrated · Succession always present
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