Executive summary · start here
Africa's venture record: a scorecard
Who sets the price, what customers already pay, and whether money flows through the product decide which African startups survive and which make money
Why this exists
Between — and —, investors put — of venture equity into African tech startups, and billions more in debt. That money is tracked closely: every round is counted and ranked by country, sector and stage. What it bought is not. Shutdowns are reported one at a time, profits rarely, and there is no common, company-by-company record of which funded startups are still standing, which make money, and why the rest did not. Without that record, each new fund relearns the same lessons with new money.
This is that record for the companies that raised the most. It follows every startup that raised a single round of — or more in —, — in all, across Kenya, Nigeria, Egypt, South Africa and — other countries, to where it stands in —. Their largest rounds alone add up to —.
The method is qualitative first, then quantitative. Each company is read as a case: what it sells, who sets its price, how its customers pay, how it is funded and what happened to it, with a source for each. Every case is then coded by hand on the same traits, and the codes are counted across the whole sample. The cases supply the reasons; the counts show which reasons repeat across countries and which were one-offs. The sample is too small for statistics in the formal sense, so the counts are evidence, not proof.
What it finds, in one line. — companies have failed or are distressed and — have published a profit, and neither is spread evenly. Failure clusters in companies that must match a price someone else already set while carrying costs their rivals do not. Profit clusters in companies that charge less than customers already pay, collect in small repeated amounts, and earn on the money that flows through the product.
Companies tracked—
Largest-round money—
Failed or distressed—
Published a profit—
Ten findings
Each number is computed from the company-level data below. Failed means shut, in administration or liquidated; distressed means a weak merger, a deep down round, an insider buyout, an asset freeze or abandoning the core business.
1. B2B distribution and logistics hold most of the losses
— of —distribution and logistics companies failed or distressed
Companies that buy goods and deliver them to small shops (Twiga, Wasoko, MaxAB, Capiter, Alerzo) or run trucks and delivery for them (Sendy, Lori, Kobo360). In every other sector combined, — of — failed or are distressed. Of all the money raised by companies that later failed or became distressed, — went to these two sectors.
So: supplying informal shops and moving their goods is where African venture capital lost the most, in every market that funded it at scale.
2. No company that sold for less than customers already paid has failed
— of —still operating
Poor households often pay more than richer ones for the same thing: kerosene costs more per hour of light than solar, renting a motorbike every day costs more than paying it off, and a telecom's transfer fees take a bigger share of a small transfer. A company that sells the same thing for less does not have to create demand. Customers simply move money they already spend. Every one of these companies is still operating.
The opposite case is a company selling goods that informal markets already sell at the lowest price. It has no saving to offer, so it competes on price alone: — of — such companies failed or are distressed.
So: the strongest businesses here replace something customers already pay too much for. Asking customers to find new money for something new is the riskier bet.
3. Asset-heavy companies fail when the market price cannot cover their costs and they lack the pricing power to raise it
— of —asset-heavy price takers failed or distressed
Owning trucks, warehouses or power plants means high fixed costs. That works only if the price the company can charge covers them. A price taker cannot choose its price: informal rivals with no fleets or warehouses set it at a level that covers their costs, not the startup's, and if the startup charges more, customers go back to the market stall. It loses money on every sale and has no way to fix it. The one survivor, —, takes the market price too, but as the lowest-cost producer its costs fit under it. Asset-heavy companies that set their own price did far better: — of — failed (—), neither because of its assets.
This is not an argument for asset-light models. Price takers that left the trucks and stock to others did better, but — of — still failed or are distressed, and — have published a profit. Taking someone else's price caps the margin, and a capped margin cannot produce venture-scale returns, however large the company grows. Most African customers are low-income households, so the Amazon playbook of thin margins at huge scale has not worked here: Jumia, the continent's best-known attempt and outside this sample, still loses money every year more than a decade after it launched.
So: the test is not how many assets a company owns but whether it can set a price that covers its costs. Without that pricing power, asset-light or not, it is at best a steady, low-margin business: worth backing with debt or private equity, which seek steady returns, but not with venture capital, which needs a few companies to return many times the money.
4. Selling an essential need does not protect a company when the existing price is already the lowest, especially in food and household goods
— of —essential-need price takers failed or distressed
Food and household goods are as essential as energy, and demand for them never fell. But informal markets already sold them at the lowest price. That is why "disruption" failed here. Twiga used apps, data and its own trucks and warehouses to cut out the middlemen between farms and market stalls, yet the produce was already sold at a price informal traders had driven to the floor. However much technology a company deployed, there was no saving to offer customers and no margin left for it to capture.
Energy shows the other side. It is just as essential, but what customers already paid for it, kerosene and diesel, was expensive. Solar companies such as d.light, M-KOPA and Sun King could charge less than that and still keep a margin. Of the companies selling an essential need for less than customers already paid, — of — are still operating. Being essential guarantees demand; the price customers already pay decides whether there is money in it.
So: an essential need is an opportunity only where customers currently overpay for it. In food and household goods they rarely do: informal markets have already pushed prices to the floor, and no technology can capture a margin that is not there.
5. Low-income customers can carry a business when they pay in small, frequent amounts
— of —companies with recurring payments failed or distressed
Most customers in this sample are low-income households and individuals, or small traders, with little cash on hand at any one time. They can rarely pay a large sum up front, but they can pay a little every day, week or month, or a small fee on each transaction. Companies built around those payments failed far less often than the rest, where — of — failed or are distressed. Small, regular payments also make revenue predictable, so a company can borrow against it and survive a funding round that comes late. Of the traits that come from how a business is designed, this one separates survivors from failures the most.
So: with mostly low-income customers, how they pay matters as much as what they buy. A business that collects in small, frequent amounts is far more likely to last than one that needs a large single payment.
6. Companies that handle their customers' money survive far more often
— vs —still operating, with and without a payments or credit product
A company handles its customers' money when its product processes their payments or lends to them: a wallet, a card machine, a loan, or a phone or motorbike sold on credit. Of the — companies that do, — failed or are distressed. Of the — that do not, — did. The gap holds within each kind of business: software, marketplaces and physical businesses all fail far less often when payments or credit run through them, as the product architecture section below shows.
So: the most useful question to ask of any startup in this market is whether money passes through its product and whether it earns on that flow.
7. Every company with a published profit earns by moving or lending money
—companies with published profits
They are —. Some are pure finance (payments, lending); the others sell a phone, motorbike or solar kit on credit and earn on the repayments. — of them, —, fund themselves by borrowing against the assets they finance or the loans they have made, and no company in the sample with that kind of debt has failed. No healthy company in distribution, logistics, health, software or consumer apps has published a profit.
So: in this market the product often wins the customer, but the financing makes the money.
8. The highest valuations go to payment networks, but most profits come from lenders
—companies valued at $1bn or more (unicorns)
— of them have payments at their core. Only —, —, have published a profit. Meanwhile — of the profitable companies, —, have never been valued at $1bn. Kenya has — unicorns and — profitable companies.
So: a $1bn valuation shows that investors expect growth, not that the company makes money. The quieter lenders are the proven earners.
9. The funding pullback did not cause the failures; it exposed businesses that only survived on investors' money
—years, the median gap between a company's largest round and its failure or distress
Many of these companies spent each round covering losses that their own sales could not, so they needed the next round before the last one ran out. That usually took about three years. When investors pulled back in 2022 and 2023, the next round did not come, and — of the — failures ended at exactly that point: a round, loan or rescue that did not arrive, or bills and payroll that could not be paid. For these companies, more money would mostly have delayed the end. The same drought hit every company in the sample, yet every company that sold for less than customers already paid, and every company with a published profit, came through it. Companies whose largest round came in 2023 have only now reached the three-year mark: — of — have failed or become distressed so far.
So: a funding drought is a test, not a cause. Many good companies still need more money before they break even, so the question is not whether a company could survive without its next round. It is whether it is on a credible path to break even: whether each round brings it measurably closer to covering its costs, or only buys more time. When a failure is blamed on a funding drought, it often means the second. Investors had stopped believing they would get their money back, and another round would only have extended the runway to an end that was already coming.
10. About one failure in five combined a governance breakdown with a business that could not pay for itself
— of —failures with a governance breakdown
- Gro Intelligence (Kenya) sold agricultural and climate data to large companies. In 2024 its board replaced the founder; it could no longer pay staff and closed within months, amid reports that regulators were examining what investors had been told.
- 54gene (Nigeria) built a large biobank of African DNA to sell research access to drug companies. Deals came slowly while its labs and staff were costly; the founder left in 2022 amid leadership turmoil, and it could not raise again.
- Capiter (Egypt) grew in two years to thousands of staff and hundreds of trucks supplying small shops. In 2022 the board removed both founders, one later admitted it owed more than it owned, and buyers walked away amid legal fights. It was liquidated.
- Dash (Ghana) raised one of Africa's largest seed rounds to link mobile-money wallets across countries, but never earned revenue. Audits found its user numbers inflated and tens of millions of dollars missing; the founder was fired.
Governance did not create the weak business underneath; it hid it until there was no time left.
So: judge the people and the business model together. A governance breakdown is often a sign that the business underneath is weaker than it looks.
The blues: every profit comes from a money business
The — companies with published profits have one thing in common: each is either pure fintech or fintech wrapped around a real product. OPay, FairMoney and MNT-Halan move or lend money. M-KOPA, Watu and d.light sell a phone, a motorbike or a solar kit, but earn on the credit attached to it: the product wins the customer, and the repayments make the margin. The pattern holds well beyond the six. Companies with a financial product at their core were hit — of — times; companies without one, — of —. Of the companies that wrap credit around a real product, — of — have been hit.
Every company, by business model
Published profitOperating, verdict pendingDistressedFailedUnicorn: valued at $1bn or more
What the blues share
| Company |
Country |
Model |
What it sells |
Cheaper than today |
Recurring payments |
Asset-backed debt |
Published profit |
- The same customer. All six sell to the mass market, low-income households, informal workers and small traders, and are paid in small, frequent amounts.
- The same engine. They earn from the stream of payments, as a fee on each transaction or interest on each instalment, not from a margin on goods. Where there is a physical product, it is the hook and the collateral, not the profit centre.
- The same funding trick. The payment stream is what they fund themselves from: receivables sold to investors (d.light), debt secured on devices and bikes (M-KOPA, Watu), loans packaged and sold (MNT-Halan), and customer balances and deposits (OPay, FairMoney).
- The same pricing position. Each charges less than what customers paid before or replaces something worse, such as kerosene, daily rental, bank fees or an informal lender. None is a price taker.
What this means for a fund. In this record, the financial layer is where African consumer businesses make money. A hardware, energy or mobility company without it is betting on product margins that no healthy company in the sample has yet shown it can earn; with it, the same company joins the only group that has published profits.
The greys: verdict pending, but not equally
Grey means still operating with no published profit, so the outcome is not known yet. Sorting the greys by the traits of the blues and of the failures splits them into three groups. This ranks the odds for each group; it is not a forecast for any single company.
What kind of product: the money layer
Every company is coded by what its product actually does, layer by layer: software or data (a system of record, a tool or content), a marketplace that matches buyers and sellers, payments, credit or insurance, and physical operations (goods, fleets, stores, plants, farms). The combinations sort the whole sample. The layer that matters is money: companies whose product moves money or lends it were hit — of — times, and they include every published profit.
Same base, with and without a money layer
Every company by product architecture
Published profitOperating, verdict pendingDistressedFailedUnicorn: valued at $1bn or more
- A system of record on its own is fragile. Software or data sold by itself failed three times in ten (Gro, Okra, WhereIsMyTransport), and none of it has published a profit. The same software becomes sturdy when money runs through it: Yoco's point-of-sale software takes card payments, Dopay's payroll pays the wages, CarePay's health platform moves the claims.
- Payments are the safest single layer. The one payments company that failed, Dash, never charged for its product and collapsed amid a governance breakdown. Most of the unicorns sit in payments, with or without credit on top.
- Credit works when it sits on the asset, not on the goods. Credit secured on a phone, motorbike, car or solar kit has not lost a company, and it holds half of the published profits. Trade credit added to low-margin distribution did not save Alerzo: the credit has to finance something customers already save money on.
- Marketplaces need a money layer more than most. Matching trucks, shops or bus seats without owning the transaction failed most often of all the asset-light models. The two marketplaces that also lend, Autochek and Gozem, are both still operating.
- Physical operations are where the losses are, unless credit comes with them. Owning goods, fleets and stores without a money layer accounts for about half of all failures in the sample; physical products sold on credit account for none.
The unicorns: who was valued at $1bn, and what that bought
— companies in the sample have been valued at $1bn or more. — of them have a money layer; the one that did not, Swvl, is also the only one that collapsed after its valuation. Only — publish a profit.
| Company |
Market |
Product architecture |
Valuation |
Basis |
Where it stands |
Profit |
- Unicorns are payment networks. Investors have paid $1bn-plus prices mainly for companies that sit in the flow of money for millions of people or businesses: OPay, Wave, Moniepoint, Flutterwave and Tyme. Network businesses get software-like valuations because each new user adds value and costs little to serve.
- The profit-makers mostly are not unicorns. M-KOPA, Watu, d.light and FairMoney publish profits but have never been valued at $1bn. M-KOPA reports revenue in the same range as OPay's. Lenders and asset financiers are priced like lenders, on their loan books, however well they perform.
- Kenya made money but no unicorns. Its profitable companies are all asset financiers, funded largely with debt, which builds profit rather than headline valuations. Nigeria's payment companies were funded with global equity, which builds valuations first.
- The one asset financier that became a unicorn is changing shape. Moove crossed $1bn in August 2026 not for financing cars for drivers in Lagos but for owning and running autonomous-vehicle fleets abroad. That moves it from credit on an asset toward physical operations, the category with the worst record here; the difference is that it does not have to match an informal rival's price.
- A valuation is not an outcome. Swvl reached about $1.5bn at its listing and lost almost all of it within two years. Most of the later unicorns were priced on claims of profit rather than growth alone: MNT-Halan, Moniepoint and Tyme all said they were profitable when they crossed $1bn. Moove did not, and only OPay and MNT-Halan have published the figures.
The sector league table
Every company by name, grouped into one sector scheme for the whole continent and ordered from the highest share hit to the lowest. Hover a chip for its country and what happened. The right-hand column is the sum of each company's largest round.
Published profitOperating, verdict pendingDistressedFailedUnicorn: valued at $1bn or more
The screen: what each question predicts
For each question, the share of companies hit when the answer is yes and when it is no. The wider the gap, the more the question tells you.
Who sets the price × who owns the assets
Share hit in each cell. Darker red means more of the cell is hit.
By market
Each market has a similar share of distribution and logistics companies. Kenya looks worst because its distributors owned their trucks and warehouses; most of Nigeria's and Egypt's did not, and those are mostly still running, though shrinking, pivoting or restructuring.
| Market |
Companies |
Hit |
In distribution or logistics |
Published profit |
Largest rounds ($m) |
Calls: what this record predicts
These are my own forecasts, dated so they can be checked. Each follows from a pattern above; each would weaken it if it turns out wrong.
- Distribution keeps dying, slowly. By the end of 2028, at least half of the B2B distributors still operating in this sample (TradeDepot, Vendease, Omnibiz, Remedial Health, Cartona and Brimore) will have shut, been sold below what investors put in, or left distribution for payments, credit or their own brands.
- The next published profits come from money businesses. By the end of 2028, at least two of Wave, Moniepoint, PalmPay, TymeBank, MAX and Moove will publish audited profit figures, while no distribution company or consumer app in this sample will.
- The 2023 class has not been judged yet. By the end of 2027, at least three of the companies whose largest round came in 2023 will be failed or distressed, as they reach the three-year mark.
- Exits go local. MNT-Halan listed in Cairo in 2026. By the end of 2028, at least one more company from this sample will list on an African exchange, and it will be a lender or payments company.
Where to look next
Hypotheses, not findings: places where the winning shape in this record should apply, which this sample does not yet test.
The shape that wins has four parts: customers already pay too much for something they buy often; the high price is set by a formal or monopoly incumbent, not by informal traders who are already cheap; payment comes back in small, frequent amounts; and there is an asset or a payment stream to lend against. Wave in Senegal is the purest example; M-KOPA, Watu and the solar companies are the Kenyan version. Places to test it:
- Cross-border transfers and remittances. Sending money to and within Africa remains among the most expensive in the world, and the price is set by formal operators, not informal ones: the Wave pattern, across borders. Dash failed here because it never charged customers and its governance broke down, not because the demand was missing.
- Power for small businesses. Generators set the price of electricity for millions of shops and workshops. Daystar, Nuru and Wetility show the model works for businesses, not only households.
- Owning the tools of work. Motorbikes, cars and phones financed against the asset made money in Kenya. Tricycles, delivery vans, sewing machines and farm equipment are the same shape and much less funded.
- Water and cooking fuel, with care. Poor households pay more per litre for vendor water and per meal for charcoal than richer ones do for piped water and gas. KOKO's collapse is the warning: the saving must not depend on a subsidy that a government can withdraw.
What to avoid. Any plan whose margin comes from undercutting informal traders who carry almost no overhead, while you carry warehouses, fleets or payroll. It has been funded in every major market, and it has not worked in any of them.
The country scorecards
Each country page has the full company list, the reasons for every failure, the profitable companies and the method.
Method and limits
Funding total. The intro's figure for venture equity into African tech is the sum of Partech Africa's yearly equity totals for the window; it excludes debt, which Partech has counted separately since 2021.
Sample. Startups headquartered in an African country, or with one as their main market, that announced a single round of — or more (equity or debt) in —, assembled country by country from funding trackers and press reports, with each outcome checked against reporting up to —. The window stops in 2023 so that most companies have had about three years to show how they turned out. Companies headquartered and mostly operating outside Africa are left out; each country page lists them.
Coding. Each company is coded by hand on its poverty premium/penalty, whether it is a price taker, asset intensity, whether demand is an essential need, recurring payments, asset-backed debt and policy dependence. Sectors are grouped into one scheme for the continent, which differs slightly from the country pages. Each company is also coded by business model: pure fintech (payments, lending, banking, insurance, investing), fintech wrapped around a real product (credit or payments attached to a device, vehicle, solar kit, farm inputs or health service), or no financial product. Each company is also coded by product architecture, from five layers: software or data, marketplace, payments, credit or insurance, and physical operations; trade credit that sweetens a sale of goods counts as credit only in the architecture, not as a financial product at the core. Unicorns are companies valued at $1bn or more in a priced round, a listing or a disclosed filing at any point, using the most recent such valuation. Profitable means published profit figures from a company that is otherwise healthy; claims without figures do not count.
Limits. This is a small, hand-built sample, not a census, and the coding is my own judgment, open to challenge row by row. Operating is not the same as a good return; many survivors raised again at lower valuations or have little public data. Selection matters: only companies that raised large rounds are here, so the record says nothing about the many that never got that far.
About this research. This study is my own independent work. I did it because billions have gone into African startups, and the record of what that money built is thin. Comments, corrections and conversations are welcome: Peter Muiga, pm@curatedventures.africa.
Curated Ventures is not a fund; it's where I publish my thinking as I move into venture investing. I am open to conversations about the research, and about working together.