Cloud Commons Labs · Project 01
A mobile observability engine that detects and classifies behavioural data flows from mobile applications, giving Canadians a device-level view of how their apps participate in the personal data economy.
Built by Cloud Commons Labs. All analysis happens on-device via local VPN interception: no payload inspection, no data transmitted without consent. Opt-in structural profiles contribute to a national picture of Canada's app-layer ecosystem.
Stage
Phase 0
Platform
Android First
Data Model
On-Device · No Payload
Pipeline
CCC Contributor
What It Does
The personal data economy has an observation problem. Platforms that operate advertising and analytics infrastructure can see exactly what behavioural data flows where: who generated it, where it went, and what it was worth. Users, researchers, and regulators cannot. LEON explores whether a mobile device can serve as an independent observatory on the same flows.
LEON uses a local VPN interception architecture on Android to capture outbound network traffic metadata, map it to known data infrastructure, including advertising networks, analytics platforms, and third-party SDKs, and classify behavioural data flows in real time. It correlates these network observations with device sensor access to produce a behavioural data profile of each application. No payload inspection. No data leaving the device without consent.
The result is not a score or a warning. It's an instrument. One that surfaces the same structural picture of the personal data economy that platforms have always had, returned to the person the data belongs to.
Build Plan
LEON is built in clearly sequenced phases, each with defined acceptance criteria. Phase 0.5 answers the core research question: can a phone reliably observe and classify its own behavioural data flows without inspecting encrypted payloads? Each phase unlocks the next.
// Phase 0 ·2–3 Weeks Dev
On-device audit of app permissions and ad tracking settings. Plain-language exposure report. Duolingo-style streaks. No account required. Ships fully offline.
// Phase 0.5 ·3–5 Weeks Dev
Android local VPN proxy captures per-app domain calls. On-device classification using public tracker lists. Real-time LeonBark alerts. Per-app dashboard.
// Phase 1 ·4–6 Weeks Dev
Privacy routines ("Secure Me Now"). Broker opt-out launcher for Canadian + US data brokers. Camera/mic activity monitor. Data Value v1.
// Phase 2 · Pipeline Contribution
Opt-in anonymous structural profile contribution to Cloud Commons Canada. Aggregated into national exposure map published openly. No paywall.
Market
Canadians with no independent view of their app data flows
Average apps per Canadian smartphone, most transmitting telemetry
Civic observatories of Canada's personal data economy
Platforms that operate advertising and analytics infrastructure maintain the only comprehensive observatories of behavioural data flow. They can see what data is collected, by whom, at what scale, and to what end. Users, researchers, and regulators operate blind. LEON is a prototype attempt to build an observatory on the other side.
Federal privacy law reform (Bill C-27), the CPPA, and sustained media attention to data practices have created real regulatory and public appetite for transparency infrastructure. LEON addresses a gap that no existing Canadian tool fills: built in Canada, analysed on-device, governed in the public interest.
Funding
LEON has two distinct funding pathways that are not mutually exclusive.
Equity Investment
Commercial privacy tool with freemium model, API licensing for researchers and institutions, and a data-value product layer. Labs structure supports equity investment and co-founder arrangements.
Grants
LEON's public-interest data contribution function creates genuine eligibility for NRC IRAP, CDMN, digital-sovereignty grants, and civic-tech funding streams. CCC's non-profit status provides additional credibility for public-interest funders.
Labs' partnership with Cloud Commons Canada and the operating principles in the inter-entity agreement are designed to make mission drift structurally difficult, not just culturally discouraged. For funders who care about where their money ends up, that structure is worth understanding.
Read the governance structure →