Bissap.ai Applied AI Lab

AI that does
the actual work.

Bissap.ai — Applied AI Lab, built in Africa

We help African companies find where AI pays off, then build it: agents, knowledge systems, vertical products and private infrastructure they own.

Start a project
Hands sorting dried hibiscus calyces in a woven basket at a West African market
Bissap — sorted by hand from Dakar to Bamako. A local ingredient with a global taste. So is our AI.Fig. 01
(01) Point of viewBissap.ai

Most AI is built in San Francisco, for San Francisco. Here, customers switch between three languages in one sentence, pay by mobile money and work through power cuts. We build AI for that reality, then hand you the keys.

Built here, for hereStrategy, engineering and operations by a team that lives the same constraints as your customers.
Model-agnosticFrontier APIs when they fit. Open-weight models on your own hardware when they don't.
Measured, not demoedEvery system ships with evaluations tied to a business number we agree on before we build.
(02) Why AfricaThe continent, in data

The next billion users won't type in English.

They'll speak, in Bambara, Wolof, Hausa, Swahili and French, often in the same sentence. Most AI wasn't built for them. Ours is.

1.5B

people, on the youngest continent on earth.

A median age around 19. The workforce of this century is growing up here, on mobile first.

2,000+

languages spoken across the continent.

Global models cover a handful well. We build for the ones your customers actually use, in text and in voice.

≈½

of the world's mobile money accounts.

Africa skipped the bank branch and built mobile money. It can skip the legacy AI stack too.

01020304
Sources: UN World Population Prospects 2024 · Ethnologue · GSMA State of the Industry Report on Mobile Money
(03) ServicesSix disciplines
(04) Private AISovereign by design

Your models. Your servers. Your rules.

An engineer walking between server racks in a data centre

For banks, telcos, hospitals and governments, sending citizens' data to a server abroad is often not an option, and increasingly not legal. We run AI entirely inside your perimeter.

Data stays homeInference, embeddings and logs stay on your hardware or an in-country cloud.
Predictable costFixed infrastructure, priced locally, instead of per-token bills in dollars.
Fully operatedSizing, deployment, monitoring and model upgrades, handled by us.
(05) ApproachFrom question to production

From question to production.

Short loops, measurable checkpoints. Each phase ends with something you could take elsewhere, so you're never locked in.

Keep scrolling
01Around 2 weeks

Discover

Interviews, data and systems audit, use-case scoring. You leave with a roadmap.

022–4 weeks

Prototype

A working pilot on your real data, measured against the metric agreed up front.

031–3 months

Build

Integrations, security, guardrails and interface, deployed where you choose.

04Ongoing

Run

Monitoring, evaluations and upgrades, or a clean handover to your team.

(06) SectorsWhere we work
A smiling woman farmer recording a voice note in a millet field at golden hour
  • Finance & Mobile Money Agent-network reconciliation, fraud, KYC
  • Telecommunications Care in local languages, churn, ticket triage
  • Healthcare Records search, clinical summaries
  • Agriculture Voice advisory, prices, weather, credit
  • Retail & Commerce Catalogue, conversational sales
  • Public Sector Citizen services, sovereign by law

Built for the languages your customers speak. French, English, Arabic and local languages such as Bambara, Wolof and Swahili, in text and in voice.

(07) Working togetherThree ways in
EngagementDurationWhat you get
Readiness Sprint2–3 weeksData and process audit, scored use-case portfolio, costed 90-day roadmap, executive briefing.Book a sprint
Pilot to Production6–16 weeksOne high-value use case taken from pilot to production, with evaluations, guardrails and handover.Scope a build
Lab on RetainerMonthlyDedicated lab capacity, private AI hosting and operations, continuous delivery and quarterly reviews.Talk partnership
(08) QuestionsAsked often

Before you ask.

We don't know where AI fits yet. Is it too early?

No. Most engagements start there. The Readiness Sprint answers "where does AI actually pay off for us?" with evidence from your own data and processes.

Does our data have to go to an external provider?

No. We're model-agnostic. When cloud APIs fit your risk profile we use the best available models; when they don't, we deploy open-weight models on your own infrastructure.

What hardware does private AI require?

It depends on workload and volume. Many use cases run on one or two modern GPUs. We size it during discovery and deploy on-premise, in a local datacenter or on dedicated cloud GPUs.

How do you prove it works?

We agree on a business metric and a quality metric before building. Every system ships with an evaluation suite, so quality is measured continuously rather than judged by impression.

Do you work across Africa?

Yes. We work with teams across the continent, on site or remotely, and with international companies building for African markets.

Who owns what you build?

You do: code, prompts, fine-tuned weights and documentation. We train your team to run and extend it.