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Overview

A Germany-based client wanted to build a centralized AI-powered Lost & Found SaaS platform that works as a digital “lost and found box” for large organizations such as airports, universities, shopping malls, and events. The goal was to eliminate the chaos of manual reporting by building a multi-tenant Lost & Found software where users can log lost items, organizations can manage found items, and AI can automatically match them for quick recovery. Bacancy’s AI engineers, software developers, and cloud experts collaborated to design and deliver a production-ready Lost & Found SaaS with secure multi-user access, real-time notifications, and AI-powered smart matching.

Technical Stack

  • React.js
  • Next.js
  • Tailwind CSS
  • Node.js
  • Express.js
  • PostgreSQL
  • MongoDB
  • NLP
  • AWS Lambda
  • AWS RDS
  • AWS S3

    • Industry

    Public Services

  • region

    • Region

    Germany

  • project-size

    • Project Size

    Non-Disclosable

Highlights

Built a multi-tenant SaaS platform that is usable by airports, universities, and events.

AI-powered smart matching connects reported lost items with found item records.

Real-time notifications and status tracking for users and admins.

Centralized admin dashboard for organizations to manage multiple branches.

Challenges & Solutions

Match vague lost item descriptions with found items

  • Solution: ntegrated AI-powered NLP and image recognition that analyzes both text descriptions and uploaded photos to improve accuracy in matching, even when details are incomplete or unclear.

To ensure multiple organizations could use the same software securely

  • Solution: Our expert software developers designed a multi-tenant SaaS architecture with strict role-based access control. Each organization operates in an isolated and secure environment while sharing the same underlying platform.

Slow manual communication between finders and owners

  • Solution: Real-time notifications, automated email and SMS alerts, and secure in-app messaging were implemented to speed up communication and enable verified users to coordinate recovery efficiently.

Had to handle large-scale data of items and reports efficiently

  • Solution: We implemented A cloud-native architecture on AWS using RDS for structured data, S3 for image storage, and scalable APIs to ensure consistent performance and reliability under high load.

Core Features

  • Easy submission with description, image, and location
  • Staff or users can log items for organizations
  • Smartly pairs lost and found reports
  • Real-time updates for potential matches
  • Supports multiple organizations under one platform
  • Insights for admins on item recovery rates and reports
  • no.-of-resources

    • No. of Resources

    05

  • time-frame

    • Time Frame

    February 2025 – July 2025

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