Keep your data
on the continent.
Our intended service processes and stores data in Africa. We’ll explain operators, access, retention and backups before the pilot.
African data.
African ground.
Your customers are here. Your AI should be closer, too. We’re building around processing and storage in Africa.
Our planned service commitment
Keep your data
Less distance.
More momentum.
Closer compute can shorten the network path. Model size, routing and load matter too. We’ll publish measured latency before making performance promises.
Your AI.
Your boundaries.
Model choice. Data control. African ground.
Planned architecture, illustrated.
GLM
Qwen
Mistralembirolabs Data policy Access rules
African hosting plannedStart with the open model that fits the job. Keep your application behind one familiar interface.
Our hosting commitmentA commitment
you can inspect.
Hosting locations
We’ll name the countries, facilities and operators before the pilot. The illustration does not identify deployed locations.
Data handling
Processing, storage, retention, access and backup terms will be explicit. Cross-border dependencies will be disclosed.
Performance evidence
We’ll measure real requests from regional user locations. Lower latency is a goal today, not a guaranteed result.
The wider workflow
Your app, third-party tools and tracing systems have their own data flows. African inference alone does not establish residency for the whole application.
Today’s waitlist
This marketing site and signup service have their own privacy notice. They do not promise African data storage.
A different starting point.
Start with where your data belongs,
then choose how you build.
Swipe to compare approaches
| What matters | Embiro Labs Planned service | Global inference API | Self-hosted models |
|---|---|---|---|
| Data location | Africa processing and storage planned | Check the provider and region | Defined by your deployment |
| Model choice | Curated open-weight candidates | Depends on the provider catalogue | You select and operate models |
| Operating effort | Managed service is the goal | Provider-managed inference | Your team runs the infrastructure |
| Regional latency | Lower latency is the design goal | Measure from your user locations | Depends on placement and capacity |
| Available today | Waitlist; pilot being scoped | Varies by provider | After you provision and operate it |
A comparison of approaches, not a benchmark or assessment of any individual provider. Actual terms and capabilities vary.
Build closer. Be here first.
Tell us what you need from African AI infrastructure.