Data-rich platforms in production
Flame and Student Portal generate structured, operational data every day. We understand data quality, access control, audit trails and the realities of running systems in production.
Emerging technology · AI · IoT · Data
AI, IoT and data intelligence for African industry
BackSpaceStudios is a scientific and technology company. Our platforms already generate and process data at scale. We are now extending that capability into AI-assisted decision-making, IoT integration and advanced data intelligence — built for the realities of African operations: intermittent connectivity, mixed data sources and real-world constraints.
Our approach pilot-first · data-grounded · built to operate, not just to demo
Where we are, and where we're going
We are not claiming a decade of AI research. We are claiming something more useful: a track record of building and operating real systems, with real users and real data, and the engineering discipline to extend that into AI, IoT and data intelligence. We are honest about what we have done, what we are building, and what we are learning.
Applied AI and IoT pilots
Predictive maintenance, anomaly detection, document automation and sensor integration. We start with a focused use case, prove value, then scale what works.
Data infrastructure for African conditions
Pipelines and dashboards designed for low bandwidth, mixed data sources and intermittent connectivity — not just ideal cloud environments.
Three capability pillars
AI, IoT and data intelligence are not separate products. They are layers of the same system: sensors generate data, pipelines move and shape it, and models and dashboards turn it into decisions.
Artificial Intelligence
Predictive maintenance & anomaly detection
Models trained on equipment telemetry and historical failure data to flag anomalies before they become downtime. Useful for pumps, conveyors, drills, fleets and processing plants.
Time-series modelsAnomaly detectionAlerting
Document intelligence & automation
Extract, classify and route information from contracts, inspection reports, invoices and compliance documents — reducing manual data entry and error.
Document extractionClassificationWorkflow routing
Decision-support systems
Combine operational data, rules and models into tools that help managers make faster, better-informed decisions — with the reasoning visible and auditable.
RecommendationsScenario analysisExplainability
Internet of Things
Sensor integration & telemetry
Deploy and integrate sensors for equipment, environmental and operational monitoring — from selection and installation to data ingestion and alerting.
Sensor selectionIngestionTelemetryAlerting
Edge-to-cloud pipelines
Move data reliably from remote or bandwidth-constrained sites to central systems — with buffering, compression and resilience built in.
Edge processingBufferingSecure transport
Remote monitoring & control
Dashboards and alerts that let teams monitor distributed assets and respond to issues without travelling to site — designed for low-connectivity environments.
Remote dashboardsAlertsLow-bandwidth
Data Intelligence
Data warehousing & ETL
Bring data from operational systems, spreadsheets, sensors and legacy databases into a structured, queryable warehouse — with lineage and quality checks.
ETLWarehousingData qualityLineage
BI dashboards & reporting
Operational and executive dashboards that turn scattered data into a single view of performance — production, maintenance, safety, finance, HR.
DashboardsKPIsScheduled reports
Real-time analytics
Streaming pipelines and near-real-time dashboards for operations where minutes matter — production lines, fleet dispatch, safety monitoring.
StreamingReal-timeOperational intelligence
How we approach AI and IoT
Emerging technology fails when it starts with the technology instead of the problem. Our approach is deliberately conservative: prove value on a focused use case before committing to scale.
Pilot-first
Start with one workflow, one asset, one decision. Build a working pilot in weeks, measure the outcome, then decide whether to scale. No multi-year transformation bets.
Data-grounded
Models and dashboards are built on your operational context — not generic datasets or imported assumptions. If the data isn't ready, we fix that first.
Built for African conditions
Low bandwidth, intermittent power, mixed legacy systems, limited data science capacity. We design systems that work in the field, not just in a demo.
Explainable and auditable
AI that cannot explain its reasoning is hard to trust. We prioritise models and interfaces where the logic is visible, reviewable and accountable.
Integration, not replacement
We connect to your existing SCADA, ERP, fleet management and spreadsheets — building around what exists rather than forcing a rip-and-replace.
Honest about limits
If a problem does not need AI, we will say so. If a rules-based system or a better spreadsheet solves it, that is the recommendation you will get.
What we bring
We are not starting from a blank page. Our existing platforms and engineering practice give us a foundation that many AI startups lack: experience running real systems, with real users, in production.
We operate what we build
Flame and Student Portal run in production on AWS Cape Town. We understand deployment, monitoring, backups, security and the long-term operational discipline that AI and IoT systems also require.
From sensor to interface
Backend, data pipelines, APIs, web and mobile interfaces. We can build the whole system — not just the model or the dashboard.
Kitwe-based, regionally focused
We are on the ground in Zambia's mining and industrial heartland. We can be on site, understand the context, and support systems after launch.
Emerging technology · Next step
Explore a pilot project
If you have a specific operational problem — equipment downtime, data blind spots, manual reporting, sensor data that isn't being used — we can scope a focused pilot to test whether AI or IoT can solve it. No obligation, no hype.