An AI-centred technology ecosystem — with products already in the market.
AfriStack Smart System Ltd is building an AI-centred technology ecosystem, with AfriKDP, Skilluxo and AfriAssist serving as deployed products and real-world environments for our technology.
We are actively connecting with investors and strategic partners who share a long-term view: that a company can build the intelligence layer and the applications on top of it, and that each one makes the other more valuable.
Not a company with several apps. An AI company with distribution.
AfriStack is building both an application layer with real users and an AI development programme underneath it, connecting the two through a common architecture.
A real AI programme, with measured results
Omnis is not a slide. We have trained a language model from scratch — our own tokenizer, architecture, training loop and evaluation harness — and cut held-out perplexity from 237.5 to 41.2 on consumer hardware.
See the results →Three live products, not one
AfriKDP, Skilluxo and AfriAssist each run independently on their own domain with their own users — evidence that our product-building approach works across multiple products and creates multiple distribution channels for our intelligence.
See the products →One gateway between them
Our architecture is designed around a common AI gateway and orchestration layer, allowing capabilities to be routed between external and internally developed models as they become ready. This allows us to improve or replace individual AI capabilities without rebuilding the products around them.
How it works →Real terms, already shipping
AfriKDP pays authors 85% royalties across 18+ African countries, with its own Publishing API already in developers' hands. Skilluxo protects every order with escrow. AfriAssist is an AI-powered production and business platform currently in early commercial development.
Revenue model, current and planned
Earning today: marketplace and transaction revenue across AfriKDP and Skilluxo, with AfriAssist subscriptions in early commercial development.
Planned: affiliate revenue at scale, API usage and enterprise or institutional licensing. We distinguish the two deliberately — several of these are designed, not yet proven.
A defensible target, honestly scoped
We do not claim we will match frontier labs on general reasoning. We are focusing where a specialised system can show a measurable advantage — African languages, local context and task-specific workflows — and we intend to prove it with benchmarks rather than assert it.
The roadmap →Products generate the data that improves the models that improve the products.
This is the part that does not show up on a feature list. AI calls routed through our infrastructure are measured across requests, failures, truncation and fallbacks, including provider and feature-level telemetry.
That measurement is what turns "we should use our own model here" from a conviction into a threshold. When our model clears the bar on a capability, we can move that capability in-house, with the potential for orders-of-magnitude reductions in serving cost depending on the workload.
Capital follows evidence.
Capital will initially strengthen the products, commercial systems and engineering capabilities already being developed. As measurable demand increases, it moves progressively through four phases.
Product and commercial systems
Product, growth, retention, revenue, payments and measurement.
Team and distribution
Engineering capacity, distribution, internationalisation and infrastructure optimisation.
Specialised AI
Specialised models, proprietary datasets, evaluation and inference.
Dedicated compute
Dedicated compute and larger technology infrastructure, when justified by utilisation and economics.
Dedicated compute and owned infrastructure are scaling milestones, not prerequisites for proving the business. We are not presenting the long-term infrastructure roadmap as current infrastructure, and we are not raising to buy hardware ahead of the utilisation that would justify it.
African foundation. Global ambition.
AfriStack was founded in Africa because exceptional technology can originate anywhere. Our market is not limited to Africa.
As we enter our next stage of growth, AfriStack is preparing for an international corporate structure and expansion strategy designed to support global investment, international partnerships, payment infrastructure, enterprise relationships, U.S. market expansion, global talent and international customers.
Investment structure
AfriStack is raising up to $2,000,000 in growth capital to accelerate the next stage of product growth, commercial expansion, AI engineering and internationalisation. Capital will be deployed progressively across measurable milestones, with larger infrastructure commitments made when utilisation, demand and economics justify them.
The raise supports the scaling of AfriKDP, AfriAssist and Skilluxo, the continued development of the Omnis AI programme, engineering capacity, distribution, payment infrastructure and specialised AI capabilities.
Full terms, the financial model and the legal data room are shared with qualified investors under NDA.
- Registered company: AFRISTACK SMART SYSTEM LTD, RC 9646667, Osun State, Nigeria
- Clear, published use of funds and milestone-based capital deployment
- Regular reporting on Company and product performance
- Material risks disclosed plainly, alongside the opportunity
Where the business actually stands.
Recorded figures, not projections. These are the same numbers in our investor materials, updated together.
AfriKDP
| Total entities / accounts recorded | 266 |
|---|---|
| Active book assets | 282 |
| Books sold | 54 |
| Paid orders | 62 |
| Recorded platform revenue | ₦246,675 |
Skilluxo
| Total users | 34 |
|---|---|
| Freelancers | 24 |
| Active gigs | 10 |
| Open disputes | 0 |
Skilluxo remains an early marketplace and is currently focused on increasing buyer demand, project volume and repeat activity.
AfriAssist
Live AI production and business platform in early commercial development.
Omnis
AI research and development programme covering model training, adaptation, evaluation, agents, inference and orchestration.
Metrics updated September 2026. Selected commercial evidence — payment records, reconciliation and client mapping — is available during investor due diligence. Detailed financial information and projections are provided in the investor materials rather than published here.
The next stage is measurement, not promises.
We would rather name the open questions than let an investor find them. These are the six our next phase is built around.
Acquisition
Can we acquire customers consistently, and at what cost?
Retention
Do users continue using our products after the first transaction?
Conversion
Can usage translate into recurring revenue rather than one-off sales?
Unit economics
What does each product contribute after direct costs?
AI performance
Where do our specialised systems create a measurable advantage over a general model?
Infrastructure economics
At what point does owning more of the AI stack become economically justified?
What is included.
A complete, nine-volume document set covering the company, the technology, the numbers and the risks.
Read our company updates →- Executive summaryInvestment overview and the thesis in short form.
- Investment opportunity & structureTerms, mechanics and participation.
- Company profile & roadmapProducts, technology and the AI roadmap.
- Financial informationCurrent position and projections.
- Legal documentsIncorporation, resolutions and agreements.
- Investor rights & responsibilitiesWhat you get and what is expected.
- Risk disclosureEvery material risk, stated plainly.
- Investor operations manualHow the relationship runs in practice.
- Templates, appendices & data room checklistEverything needed for diligence.