Public and donor-funded infrastructure projects lose value when payment runs ahead of physical progress. The cause is rarely a single bad actor. More often, the people approving a payment simply cannot see the site, and must rely on a contractor's photo, a consultant's form or a progress certificate.
The Problem: Four Gaps Between Payment and Proof
- Unverifiable evidence. Progress photos can be old, taken elsewhere, or reused across projects.
- Infrequent site visits. Distance, cost and security limit how often officers inspect sites.
- Silent communities. People living near a stalled site see problems first, but fear being identified if they report.
- Scattered records. Progress, evidence, QA decisions and payments sit in separate files and offices, so no one sees the whole picture.
How ProveTrack Works
ProveTrack is one platform with three parts: a staff web dashboard, an Android app for field officers and citizens, and a public web portal for anonymous citizen reports. Every project follows the same five steps:
- Report. Field officers log progress; citizens report problems or progress anonymously.
- Verify. Evidence is accepted only from inside the project's GPS site boundary (geofence).
- Evidence. Live-camera photos are stamped with location and time and checked for duplicates.
- Track. Projects sit on one map and dashboard, each with a health score measured against its own plan.
- Resolve. QA approves against a checklist, finance releases the tranche when every rule passes, and citizens follow the outcome with their tracking code.
Geo-Verified Field Evidence
Field officers capture evidence in the app, which works only inside the project's site boundary and only with the live camera, so gallery photos cannot be uploaded. Each photo carries its GPS location and time, and images already used on another project are flagged. At remote sites with no signal, evidence is stored on the phone and synced later with its original time and location.
Anonymous Citizen Reporting
Anyone can report on a project without an account, name or phone number. The reporter receives a private tracking code, which is the only link to the report. No IP address is stored, and photo location data is stripped on upload. Staff triage each report: they can request a field visit, reply to the citizen, or escalate it to a fraud flag that blocks payment.
QA Review and Rule-Based Payments
QA officers score each milestone against a checklist, and every required item must reach the milestone's pass mark before it can be approved. Finance officers then run the release check: a tranche becomes eligible only when the milestone is approved, the evidence is verified, independent validation is complete, and no fraud flag is open. Finance cannot override the check.
Safeguards Built In
- Separation of duties: nobody can approve their own submission, and whoever raises a fraud flag cannot clear it.
- Tamper evidence: an append-only audit trail, and one-click PDF reports that each carry a SHA-256 fingerprint.
- Abuse limits: repeat citizen reports from one source are limited, and a project's risk rises only when several separate people report.
- Role-based access: each role sees only what its job needs.
- Data ownership: the client owns all data, and ProveTrack can run on BravEdge's cloud or on the client's own servers.
Technology
ProveTrack uses Django and Django REST Framework with GeoDjango for site boundaries, a React staff dashboard, and a React Native Android app. Background jobs run on Celery, and the whole stack is packaged with Docker for deployment on a cloud server or on-premises.
Conclusion
ProveTrack closes the gap between what a payment record says and what is actually on the ground. Evidence must come from the site, citizens can raise concerns safely, and money moves only when every rule has passed.
The platform is ready for pilot deployment with government MDAs, project management units and development partners.
Interested in piloting ProveTrack?
BravEdge runs pilots of ProveTrack on a small set of live projects, so organisations can judge it on real results before scaling up.
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