The firm has not disclosed the fund’s size, leaving the amount of capital available through the new vehicle unconfirmed. Enza previously raised $58 million across its first two funds.

The AI Africa Fund will focus on companies developing technology suited to African languages, local data, customer needs, and infrastructure conditions.

Enza’s strategy centers on commercially useful applications and specialized systems rather than financing the costly development of frontier models that compete directly with the largest global AI developers.

Founded in 2019 by Mike Mompi, Sir John Lazar, and David Cohen, Enza says it has made 75 investments in 47 companies across nine African countries.

Managing Partner Mike Mompi told TechCabal that the firm had completed 11 AI investments and was working on its 12th, giving the specialist fund an existing base of investment experience in the sector.

Enza’s selection criteria emphasize founders with detailed knowledge of their markets and businesses with advantages that competitors cannot easily reproduce.

These include exclusive datasets, established customer relationships, and software integrated into customers’ daily operations.

In its published investment thesis, the firm argues that cheaper software development increases competition and makes these commercial advantages more important.

Operating costs will also influence investment decisions because running AI models creates recurring expenses that can weaken profitability as usage grows.

Enza is looking for companies with strong margins or a credible route to achieving them, with Mompi telling TechCabal: “Net profit margin and free cash flow matter even more than gross margin.”

The firm’s investment in Aethex AI illustrates its focus on the practical barriers to enterprise adoption.

Aethex develops voice AI for African and Middle Eastern markets, addressing differences in accents, dialects, and language use.

Enza’s investment commentary also identifies response speed and integration with business systems as essential requirements for reliable automated customer service.

For banks, insurers, telecommunications providers, and other service businesses, the commercial value of these tools depends on completing customer requests accurately and reducing the cost of serving them.

Enza notes that an automated interaction that fails and requires a human agent can add expense without resolving the customer’s problem, making operational performance central to the investment case.

Enza also supports access to technical expertise through its office of the chief technology officer and its involvement in AI Tinkerers communities in Nairobi, Lagos, Cairo, and Johannesburg.

These activities connect engineers and founders with peers and technical partners as they develop products for commercial use.

For founders seeking backing, Enza’s published strategy places customer access, proprietary data, and integration with business operations at the center of the funding proposition.

Its focus connects AI investment to a practical business requirement: building products that customers can use reliably and that companies can deliver profitably under local operating conditions.