Data That Builds Better Places
Kogenta Connect for Local Municipalities.
The Challenge: Decisions Without Complete Insight
Municipalities and regional authorities are tasked with shaping vibrant, sustainable, and inclusive communities — yet the data they rely on is often incomplete, outdated, or locked in silos.
Common challenges include:
- Limited visibility into how people move through and use different areas of a city or region
- Unclear understanding of who lives, works, studies, and visits local zones
- Difficulty justifying investment decisions with current, evidence-based data
- Lack of integration between transport, economic, and demographic datasets
- Concerns around data privacy and citizen consent
Without a complete picture of population dynamics and behaviour, planning can become reactive — driven by anecdote rather than evidence.
The Solution: Kogenta Connect for Municipalities.
Kogenta Connect gives municipalities a unified, high-fidelity data foundation for understanding how people, places, and services interact in the real world.
Built on the Kogenta Grid — a high-resolution spatial framework — it layers together movement, demographics, expenditure, and contextual data to deliver a consistent, privacy-safe view of activity across any town, city, or region.
Whether you’re planning transport networks, evaluating retail vitality, monitoring tourism, or supporting environmental goals, Kogenta Connect helps public decision-makers work with clarity and confidence.
Key Data Layers for Municipal Insight.
Busyness Layer
A rich, AI-driven view of how busy different areas are – hour by hour, day by day, hex by hex. By fusing multiple independent signal sources into a unified model, this layer infers real-world human activity with exceptional accuracy and consistency. No single dataset dominates the output, ensuring robust, balanced insights that can be confidently compared across locations.
Forecasted Busyness Layer
A forward-looking model that predicts human activity at an hourly level across every H3 cell on the grid. Using advanced AI to learn behavioural patterns, fill data gaps, and synthesise historical trends, this layer enables planners and analysts to see not just what is happening – but what is likely to happen next.
Origin–Destination Flow Layer
Understand how residents, commuters, and visitors move within and between neighbourhoods – identifying flow corridors, hubs, and underserved areas. An AI-enhanced, multi-modal model of movement between origins and destinations. Built on multi-modal network structures and trained on validated transport data, this layer delivers high-fidelity OD flows that reflect the real dynamics of how people travel- across modes, times, and regions.
Journey Layer
Based on detailed, individual journeys that have been anonymised and aggregated from opted-in applications, typically Transport or Panel applications and sourced via SDK where the user has opted in.
Places Layer
Identify key destinations – schools, shops, public spaces, transport nodes – and how they influence population movement. Map the surrounding ecosystem: shops, transit, dining, workplaces, and amenities – the factors that define location value. Catalogues commercial, civic and transport locations – shops, venues, schools, stations, and more – linking people movement to the points of interest in a location.
Demographics Layer
Profile population characteristics at local level. Profiles populations across age, household type, income, education and occupation – giving context to who resides in an area. Combined with Movement data, a powerful picture emerges of the demographics of the people travelling into, through and out of an area.
Expenditure Layer
Map local spending power and category-level expenditure to understand commercial health, retail leakage, and economic opportunity. Maps household and consumer spending across multiple categories – from groceries and entertainment to travel and luxury goods – providing deep insight into local purchasing power. When combined with Movement data a powerful view of the expenditure habits of the people travelling into, through and out of an area emerges.
Survey Layer
Blends large-scale survey responses and opt-in data with behavioural signals, adding qualitative understanding to quantitative data. Sourced from reputable market research partners or directly by our own survey engine. Gather local opinion through targeted SmartSurveys, capturing resident sentiment on transport, safety, amenities, or development proposals.
The Benefits.
Complete Urban Insight — See how people, places, and services truly connect- Integrated Framework — Combine multiple data sources on one spatial grid
- Comparable Across Regions — Uniform methodology across Europe, North America, Asia and Australia
- Privacy-First Approach — GDPR compliant, aggregated, and pseudonymised
- Actionable Intelligence — From dashboards to policy evidence, ready for use by planners, analysts, and elected officials
