On-device processing. Zero raw data movement. Built for the African market from the ground up — enabling behavioral fraud detection, audience intelligence, and risk scoring that respects your users.
African businesses are navigating signal loss, rising fraud, and a total absence of privacy-native infrastructure — all at the same time.
Third-party cookies are dead. Mobile IDs are restricted. African advertisers are flying blind — no reliable behavioral signal to reach the right audience, measure impact, or prevent ad fraud.
Account takeover and SIM-swap fraud is surging across Nigerian and East African banks. Existing rule-based systems can't detect the subtle behavioral patterns that distinguish a real user from an attacker.
There is no privacy-native behavioral data layer in Africa. Companies building data products are either violating user privacy or building on foreign infrastructure that wasn't designed for African regulatory context.
Clean Lava's behavioral intelligence layer powers three distinct markets — all from a single privacy-safe data foundation.
Cookieless behavioral audience segments — built on-device, shared only as privacy-safe tokens. Enables programmatic targeting, frequency capping, and attribution without exposing raw user data.
Continuous authentication using typing rhythm, swipe dynamics, and device handling signatures. Detects SIM swaps and account takeover attempts in real time — without storing biometric data.
Behavioral risk scores that help underwriters assess creditworthiness and lifestyle risk — without invasive data collection. Phone usage patterns as a proxy for financial behavior, with explicit consent.
Behavioral signals are processed on the device. Only privacy-safe tokens reach our infrastructure. Raw data never moves.
Typing rhythm, swipe dynamics, and touch patterns are measured locally — through the OEM hardware layer and the app layer simultaneously.
On-device ML converts behavioral signals into privacy-safe tokens. Raw measurements are discarded immediately after processing.
Only tokenized, aggregated, differentially-private outputs reach Clean Lava's infrastructure. No raw data ever crosses the device boundary.
Advertisers get audience segments. Banks get fraud verdicts. Insurers get risk scores. All via API — no data science team required.
Every design decision in Clean Lava's architecture starts with one question: how do we make this impossible to abuse?
Behavioral signals are analyzed inside the device's trusted execution environment. Raw touch and keystroke data never leaves the phone.
Mathematical noise is added to all outputs before they leave the clean room — making it provably impossible to reverse-engineer individual user data from aggregate signals.
Clean Lava's infrastructure never receives, stores, or processes raw behavioral data. Only privacy-safe tokens and aggregated scores transit the network.
Built from day one for Nigeria's Data Protection Act — explicit consent at every touchpoint, right to erasure, data minimization, and local processing requirements.
We're onboarding a small group of design partners in adtech, banking, and insurance. If you're building in one of these verticals, let's talk.