Tesseron Insights turns raw telecom network metadata into a standardized, privacy-compliant map of human movement and intent, at population scale, built one anonymized signal at a time.
A loyalty card or app login tells you what happens inside your own walls, and nothing about where that same person goes, or what they do, everywhere else.
Rely on sampled or surveyed data that never shows the full picture of a customer's real-world behaviour beyond their own environment.
Make large-scale planning decisions on census figures that are already years out of date by the time they're published.
Pay for reach across a digital ecosystem increasingly built on bots and synthetic traffic, with no guarantee of a real human on the other end.
Raw network metadata, anonymized and modelled into behavioural intelligence that's usable by enterprise, government and advertising teams alike.
Subscriber location and movement, resolved to a 50m × 50m grid, refreshed every 15 minutes, enhanced with telco CRM data.
App and URL-level visibility into digital behaviour, showing what people browse and use, independent of device settings or app permissions.
Near-real-time and scheduled targeted communication, delivered inside the operator environment to a verified, present human.
Devices connect to Radio Access Networks and communicate with destination servers, generating measurement reports.
A standardization node inside each operator's own firewall performs AI inference and modelling before anything is anonymized.
One-way hashing is applied to all personally identifiable information before any output crosses the operator boundary.
Anonymized, modelled data is aggregated and weighted centrally, then delivered in AI-ready formats to enterprise or government.
SHA-256 one-way hashing is applied to all personal identifiers before any processing takes place beyond the operator boundary.
Architecture is designed and operated in line with South Africa's Protection of Personal Information Act and GDPR.
Every query is authenticated, authorized and logged. Only anonymized insight ever leaves an operator's local node.
Data output independently reviewed and affirmed by McKinsey and Dentsu. In active operational use across multiple multinational enterprises.