Aroundin

Aroundin is a Alibaba/Amazon or ebay for (SMEs)Small and medium-sized enterprises. Why remain being small/medium??...A solution for scale with multiple benefits for both parties including the consumer

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Inspiration

Our inspiration stems from a paradox in modern digital life: while global e-commerce is hyper-efficient, local commerce remains rife with friction. Small and Medium-sized Enterprises (SMEs) are the backbone of local economies and the foundation of resilient communities, yet they often lack the sophisticated, affordable digital tools to effectively compete or even be discovered by nearby customers. This disconnect leads to customers bypassing sustainable, local options for convenience, inadvertently contributing to the logistics and carbon footprint of centralized supply chains.

Aroundin was conceived to solve this local discovery challenge. We were driven to create a platform that not only "finds" local shops but empowers them by simulating the kind of cutting-edge business management and customer engagement tools that only large corporations typically afford.

What it does

Aroundin is a unified, high-fidelity prototype that provides two distinct but linked experiences:

Customer-Facing Discovery Platform (CustomerView.tsx)

  • AI-Powered Search (Deep Tech):
    Customers use natural language queries (e.g., "Where can I find a small tailor to repair my vintage jacket?") which the Gemini API processes. This integration leverages the intended Google Maps grounding tool to return highly contextual, geospatially-relevant results from local shops. This shifts discovery from simple keyword matching to semantic and spatial understanding.

  • Hyperlocal Engagement:
    Features a comprehensive ShopPortfolio and an interactive ChatModal where customers can 'tag' specific products they are interested in, simulating a pre-order or detailed inquiry with the seller. Directions are simulated to open an external Google Maps link.

Vendor-Facing Business Management Dashboard (VendorView.tsx)

  • Onboarding Prototype:
    Simulates the critical customer discovery and product-market fit journey via a two-step flow: ShopCreator (template selection) and VendorDashboard (populated with mock stats, inventory, and sales charts).

  • Simulated Value:
    The dashboard is a proof-of-concept demonstrating how Aroundin provides the necessary intelligence for an SME to manage inventory, track simulated sales, and gain data-driven insights—tools essential for any business seeking to scale and achieve stability.

How we built it

We implemented a modular Single-Page Application (SPA) architecture using React and TypeScript for robust component development.

The most critical components for the Deep Tech focus are the twin engines of discovery:

  • Gemini API Integration:
    We created a dedicated services/geminiService.ts to manage the API calls. The API is used to interpret the customer's intent from the search bar. We explicitly designed this feature to leverage the Google Maps grounding tool (via the Gemini API) to find the most relevant shop from our static MOCK_SHOPS data. This feature demonstrates the fusion of AI and geospatial technology.

  • Google Maps/Geolocation Framework:
    The system relies on the browser's navigator.geolocation API to establish the user's current position. The subsequent display of a map and "Get Directions" links rely on the Google Maps platform, which is currently simulated with static images and external links due to API key requirements. This structure shows that the location infrastructure is built-in and ready for live integration.

For the user experience, we leveraged Tailwind CSS for efficiency and a modern aesthetic, using custom components (e.g., ShopCard, ChatModal) to ensure a smooth, intuitive flow between discovery and transaction. The URL query parameter ?role=vendor serves as the simple but effective routing mechanism to switch between the two primary application views.

Challenges we ran into

  • User Feedback & Proof of Concept:
    While the goal was to secure funding through a hackathon, we faced the common early-stage hurdle of reaching a broad range of SMEs to validate our interface and feature set prior to or during the short hackathon period. The lack of direct, broad market feedback meant our dashboard features had to be based on generalized SME needs.

  • API Key Restriction:
    The Google Maps integration, a vital part of the hyperlocal experience, had to be disabled. This necessitated the use of static map images and external links to simulate the full geospatial functionality, a compromise we are ready to resolve upon securing funding.

Accomplishments that we're proud of

We are most proud of developing a functioning Minimum Viable Prototype (MVP) that successfully integrates a Deep Tech AI feature into a commerce application.

  • High-Fidelity MVP:
    We didn't just deliver mockups; we delivered a navigable prototype that allows the user to experience the core value proposition—from AI-powered discovery to chat-based engagement—on both the customer and vendor sides.

  • Semantic and Spatial Search Implementation:
    Successfully designing and simulating a natural language search that intelligently grounds user intent (via the Gemini API) to geospatial location and local resources is a major technical accomplishment. This feature is the linchpin of the platform's value proposition, demonstrating a clear path to solving the friction of local digital discovery.

  • Unified Experience:
    Creating a single, high-performance application that seamlessly switches between a customer product and a vendor management tool showcases thoughtful, scalable architecture.

What we learned

We learned that for SMEs, the biggest hurdle isn't sophisticated technology, but simplicity and integration—the vendor must be able to "create a shop" and immediately see value (e.g., through the mock dashboard analytics), reinforcing the importance of a clear path to product-market fit. The exercise reinforced the need to abstract complex Deep Tech (AI/ML) into simple, highly effective user features (natural language search) that solve a tangible, everyday problem.

What's next for Aroundin

Our next steps are centered around enhanced automation and financial empowerment for local vendors:

  • Mobile-First Development:
    Full native Android/iPhone application development for on-the-go customer discovery and vendor management.

  • Transaction Analytics & AI Insights:
    Integrating with payment gateways to provide vendors with real-time transaction analytics and AI-driven recommendations on inventory and pricing.

  • Financial AI Advisor:
    Develop a feature that leverages Gemini's reasoning capabilities to analyze a vendor's simulated sales data and provide AI-guided financial advice (e.g., "Your average product margin is α, but your top-selling product is only 2α​—consider raising its price by 10%"). This directly empowers local businesses with the type of cutting-edge intelligence traditionally limited to large enterprises.

  • SMS Retrieval Integration:
    Allowing vendors to manage simple order confirmations and customer messages directly through an SMS integration, bridging the digital gap for businesses with limited existing infrastructure.

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