AI infrastructure for data intelligence.
Kognitiv Analytica builds AI systems that turn complex data into clear insights, predictions, and decisions — starting with education, and built to scale across research, business, and public services.
Data intelligence, built for institutions.
Kognitiv Analytica is an AI research and technology initiative focused on building an African AI infrastructure for data intelligence, deep data analysis, and decision support.
Our objective is to develop powerful AI systems that help institutions, organisations, researchers, and businesses transform complex data into clear insights, predictions, and intelligent recommendations.
Every product we build sits on top of the same core model — designed once, and applied wherever institutions need to understand their data and act on it with confidence.
Kognitiv Core is not a chatbot.
At the centre of our vision is Kognitiv Core — an AI model designed to analyse structured data, identify patterns, generate insights, support forecasting, and assist decision-making. It's a specialised model built to process data and produce analytical intelligence used across different sectors.
Pattern recognition
Identifies trends and anomalies inside structured institutional data.
Forecasting
Projects future outcomes from historical series using statistical and deep learning methods.
Decision support
Turns raw analysis into recommendations institutions can act on.
-H "Authorization: Bearer $KOGNITIV_API_KEY" \
-d '{ "analysis_type": "time_series" }'
// kognitiv-deep-learning-analyzer
{
"trend": "increasing",
"predicted_next": 115.0,
"confidence": 0.85,
"method": "MLP Neural Network"
}
A first, practical use case: primary schools.
As part of our early development, we are building a data analysis module for primary schools. It is not the final vision of Kognitiv Analytica, but a practical use case to test and demonstrate the power of Kognitiv Core in a real educational environment.
Turning school data into decisions.
Through this module, Kognitiv Core analyses school data such as student performance, attendance, learning progress, and academic trends — giving schools a clear, current view of how their students are doing.
It's a testbed for the broader model: the same analytical engine that reads a school's grade sheet is built to read a hospital's patient data, a ministry's census, or a company's operations data tomorrow.
performance · attendance · progress · trends
statistical + neural network
shared across every module
education is the starting point
Target clients.
Kognitiv Core is designed to serve any institution that needs to turn complex data into clear, actionable intelligence — starting with the organisations closest to our first deployment.
Primary & secondary schools
Our first deployment ground — analysing student performance, attendance, and learning progress to support teachers and school leadership.
Universities & higher education
Institution-wide analytics on academic performance, retention, and research output for administrators and faculty.
Research institutions
Deep data analysis and forecasting for research teams working with structured, complex datasets.
Public sector & government
Decision support for public services that manage large-scale institutional and citizen data.
Businesses & enterprises
Business intelligence built on the same core model — pattern recognition, forecasting, and recommendations for operational data.
NGOs & development organisations
Data-driven decision-making for organisations operating across education, health, and community programmes.
"AI infrastructure made in Africa, for African institutions — with the ability to support education, research, business intelligence, public services, and other data-driven sectors."
API reference.
Every request to the Kognitiv Core API is authenticated and returns structured JSON. Below is the current reference for conversational, analytical, and monitoring endpoints.
All requests require a bearer token and JSON content type.
Authorization: Bearer <KOGNITIV_API_KEY>
Educational Q&A and conversational tasks powered by Kognitiv Core.
{
"query": "What is machine learning?",
"model": "kognitiv-core-v2.7",
"temperature": 0.7,
"max_tokens": 300
}
{
"id": "kognitiv-abc123",
"model": "kognitiv-core-v2.7",
"choices": [{
"message": {
"role": "assistant",
"content": "Machine learning is..."
},
"finish_reason": "stop"
}],
"organization": "University A"
}
curl -X POST https://api.kognitivcore.app/v1/chat/completions \ -H "Authorization: Bearer <KOGNITIV_API_KEY>" \ -H "Content-Type: application/json" \ -d '{ "query": "What is machine learning?", "model": "kognitiv-core-v2.7", "temperature": 0.7, "max_tokens": 300 }'
Data analysis for educational metrics, student performance trends, or research datasets.
{
"data": [90, 75, 88, 92, 78],
"column_name": "grade",
"analysis_type": "full"
}
{
"id": "analysis-xyz",
"model": "kognitiv-ml-analyzer",
"choices": [{
"analysis": {
"statistics": { "mean": 84.6, "median": 88 },
"trends": ["Stable improvement"],
"forecast": [85, 87, 88]
}
}]
}
curl -X POST https://api.kognitivcore.app/v1/analyze \ -H "Authorization: Bearer <KOGNITIV_API_KEY>" \ -H "Content-Type: application/json" \ -d '{ "data": [90, 75, 88, 92, 78], "column_name": "grade", "analysis_type": "full" }'
Advanced statistical analysis and time-series forecasting using Kognitiv Core's deep learning engine.
{
"data": [
{ "timestamp": "2026-01-01", "value": 100 },
{ "timestamp": "2026-01-02", "value": 105 },
{ "timestamp": "2026-01-03", "value": 103 }
],
"analysis_type": "time_series"
}
{
"model": "kognitiv-deep-learning-analyzer",
"choices": [{
"analysis": {
"forecasting": {
"trend": "increasing",
"predicted_next": 115.0
},
"deep_learning_forecast": {
"confidence": 0.85,
"method": "MLP Neural Network"
}
}
}]
}
curl -X POST https://api.kognitivcore.app/v1/data-analysis \ -H "Authorization: Bearer <KOGNITIV_API_KEY>" \ -H "Content-Type: application/json" \ -d '{ "data": [{ "timestamp": "2026-01-01", "value": 100 }], "analysis_type": "time_series" }'
Retrieve usage, quota, and performance statistics for the institution.
{
"organization": "University A",
"quota_used": 10250,
"quota_limit": 50000,
"quota_remaining": 39750,
"total_requests_30d": 3200,
"avg_latency_ms": 210
}
curl -X GET https://api.kognitivcore.app/v1/organizations/usage \
-H "Authorization: Bearer <KOGNITIV_API_KEY>"
List supported models and their capabilities.
{
"data": [
{ "id": "kognitiv-core-v2.7", "description": "Conversational AI" },
{ "id": "kognitiv-ml-analyzer", "description": "Data analysis" }
]
}
curl -X GET https://api.kognitivcore.app/v1/models \
-H "Authorization: Bearer <KOGNITIV_API_KEY>"
Health & monitoring
Institutions can use the provided API base URL for health checks when allowed by Kognitiv.
Operational
Operational
Operational
Operational
curl -X GET https://api.kognitivcore.app/v1/health \
-H "Authorization: Bearer <KOGNITIV_API_KEY>"