RF Fraud-Detect Warehouse SaaS
Budget: ₹37,500 – ₹75,000 INR
I’m looking to have a cloud-hosted, multi-tenant SaaS platform built that combines warehouse management intelligence with a radio-frequency–based fraud-detection engine. The environment you’ll be serving is a busy distribution center where every misplaced pallet or spoofed tag has a real financial impact, so speed and accuracy are critical.
Core capability requirements
• Inventory tracking that ingests live RF/RFID reads to keep stock positions up to the second.
• Real-time alerts that fire whenever the data stream shows anomalies—unauthorized tag movement, duplicate IDs, signal loss, or any pattern we jointly define. Workers should receive push, SMS, or email notifications instantly.
• Data analytics and reporting dashboards that help managers drill down by SKU, bay location, shift, or operator to uncover fraud trends and verify process improvements.
Technical expectations
The platform must be web-based, responsive, and scalable, written in a mainstream stack you’re comfortable maintaining. Think along the lines of Node.js or Python back-end services, PostgreSQL (or similar) databases, and a modern front-end framework such as React or Vue. Low-latency socket or MQTT channels will be needed to stream RF reader events. All code should be containerised (Docker/K8s ready) for easy deployment.
Design direction
I need a fully custom look and feel that reflects our brand palette and the fast-paced, high-trust atmosphere of a distribution hub. You’ll collaborate with our designer on colour, typography, and UX wireframes, then translate those into production-ready components.
Security & compliance
Single-sign-on, role-based access, audit logs, and GDPR-friendly data policies are mandatory. If you have prior experience meeting SOC 2 or ISO 27001 guidelines, note it.
Acceptance criteria
1. A working SaaS instance deployed to our cloud account with multi-tenant onboarding.
2. Live RF data integration validated against our test readers.
3. Alert rules configurable via the UI and demonstrably triggering.
4. At least three interactive analytics views (overview, location heatmap, operator drill-down).
5. Source code, build scripts, and basic DevOps documentation handed over.
If you’ve built IoT dashboards, RFID or BLE tracking tools, or anti-fraud systems before, that background will be invaluable. Let me know your proposed tech stack, timeline, and any clarifying questions so we can get started.
Core capability requirements
• Inventory tracking that ingests live RF/RFID reads to keep stock positions up to the second.
• Real-time alerts that fire whenever the data stream shows anomalies—unauthorized tag movement, duplicate IDs, signal loss, or any pattern we jointly define. Workers should receive push, SMS, or email notifications instantly.
• Data analytics and reporting dashboards that help managers drill down by SKU, bay location, shift, or operator to uncover fraud trends and verify process improvements.
Technical expectations
The platform must be web-based, responsive, and scalable, written in a mainstream stack you’re comfortable maintaining. Think along the lines of Node.js or Python back-end services, PostgreSQL (or similar) databases, and a modern front-end framework such as React or Vue. Low-latency socket or MQTT channels will be needed to stream RF reader events. All code should be containerised (Docker/K8s ready) for easy deployment.
Design direction
I need a fully custom look and feel that reflects our brand palette and the fast-paced, high-trust atmosphere of a distribution hub. You’ll collaborate with our designer on colour, typography, and UX wireframes, then translate those into production-ready components.
Security & compliance
Single-sign-on, role-based access, audit logs, and GDPR-friendly data policies are mandatory. If you have prior experience meeting SOC 2 or ISO 27001 guidelines, note it.
Acceptance criteria
1. A working SaaS instance deployed to our cloud account with multi-tenant onboarding.
2. Live RF data integration validated against our test readers.
3. Alert rules configurable via the UI and demonstrably triggering.
4. At least three interactive analytics views (overview, location heatmap, operator drill-down).
5. Source code, build scripts, and basic DevOps documentation handed over.
If you’ve built IoT dashboards, RFID or BLE tracking tools, or anti-fraud systems before, that background will be invaluable. Let me know your proposed tech stack, timeline, and any clarifying questions so we can get started.