TualIA

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Inspiration

Small corner shops (tienditas) are the economic backbone of our neighborhoods, yet they operate in a complete blind spot when it comes to inventory management. Most merchants aren't aware that the truest path to optimization isn't just about forcing more sales, it's about buying the exact right amount of stock, finally moving away from the friction of old-fashioned, manual tracking.

We were inspired to build Tuali Growth Agent to completely shift the paradigm of traditional retail tech. True growth for a micro-retailer doesn't just come from blindly chasing higher sales volume; it comes from maximizing capital efficiency. We set out to engineer an intelligent companion that minimizes human effort while maximizing strategic decision-making, helping merchants effortlessly unlock the capital and stock trapped on their shelves. Ultimately, by automating the heavy lifting of their business, we give these hard-working shopkeepers back their most valuable asset: time to spend with their loved ones.

What it does

TualIA is an AI-powered growth orchestrator that eliminates retail friction through three main pillars:

Ultra-Simplified Inventory Tracking: Shopkeepers completely bypass entering selling prices. They only log what they bought, what they paid, and the quantity. The AI handles the rest using item velocity (sell-through rate) instead of manual margins.
The 60-Second Check-In: Every 7 days, a simple binary overlay asks the shopkeeper if a specific product sold out or if items remain, updating store inventory effortlessly.
Goal-Driven Restocking: Shopkeepers completely bypass calculating profit margins or forecasting orders. They simply type a weekly profit goal (e.g., $5,000 MXN) or tap a pre-calculated target based on their sales history.
Hyper-Local Demand Alerts: Shopkeepers no longer guess what neighbors are buying. The AI monitors real-time market data within a 500-meter radius to detect when nearby stores run out of high-demand products. It instantly alerts the shopkeeper so they can leverage their own stock to capture those lost sales, calculating their potential extra earnings and driving them to hit their weekly profit goals faster.

The AI instantly builds and pre-fills their supplier cart with the exact products and quantities needed to hit that target in one tap.

A Dual-Mode AI Orchestrator:

Proactive Mode: Runs in the background every 24 hours to automatically push actionable strategy cards (like flagging a product at risk of spoilage and suggesting a 2x1 promo) directly to the UI without the merchant having to ask.
Reactive Mode: A dedicated, context-bounded chatbot embedded straight into the dashboard that exclusively monitors goal progress and triggers real-time Hyper-Local Demand Alerts when nearby competitors run out of stock. It instantly calculates potential extra earnings, allowing the shopkeeper to leverage their own inventory to capture those lost neighbor sales and smash their weekly profit goals faster.

How we built it

We architected a modular multi-agent ecosystem powered by the Claude API utilizing advanced Tool Use (Function Calling) to seamlessly route specialized data tasks.

Frontend: Built with React and Next.js to deliver a lightning-fast dashboard, smooth overlay components for the weekly check-in, and an intuitive chat interface.

*Backend & Orchestration: Developed using a robust combination of Node.js and Python to manage the core orchestration layers and the background cron jobs that trigger the proactive recommendation loops.

Challenges we ran into

One of our biggest hurdles was figuring out how to build a highly intelligent inventory engine without forcing the user to log every single customer transaction or item price. We solved this by engineering our system to rely purely on sell-through velocity over time intervals. This required building custom constraints within our Validation Agent to accurately calculate risk, stockouts, and over-purchasing using nothing but binary data points collected from our quick weekly check-ins.

Accomplishments that we're proud of

We are incredibly proud of our proactive recommendation engine. Successfully decoupling the AI into two interfaces, where one side acts completely autonomously in the background while the other acts as a laser-focused conversational assistant, proved to be an incredible UX breakthrough. We built a solution where a merchant can completely optimize their store's cash flow in under 60 seconds a week.

More importantly, this design is a massive win for inclusion and accessibility. Many traditional corner-shop owners are older merchants who face a steep learning curve or high friction with complex digital tools. Shopkeepers don't need to navigate complex menus, read dense analytics, or change their daily routine; they can simply listen to their metrics and goals while keeping their eyes on their customers. We successfully built a solution where any merchant, regardless of age or tech-savviness, can completely optimize their store's cash flow in under 60 seconds a week

What we learned

We learned that when designing technology for busy micro-retailers, less is infinitely more. Building a generic "ask-me-anything" AI assistant actually creates user decision paralysis. By deliberately limiting the scope of our Reactive Chatbot to the merchant's active business goal, we achieved dramatically higher contextual precision, erased AI hallucinations, and built an interface that business owners can actually trust.

What's next for Tuali Radar

We want to take Tuali Growth Agent from a hackathon MVP to the open market by building deep, native integrations with B2B ecosystems like Yomp. Our immediate roadmap includes:

Live Supplier Integration: Connecting the Proactive Engine directly to corporate promotion catalogs to instantly match a shop's overstock with real-time brand discounts.
Event-Driven Hyper-Local Forecasting: Using localized, anonymous cross-store data to inject spatial intelligence into our Validation Agent. By tracking a store's proximity ratio to high-traffic hubs; such as stadiums, concert venues, and convention centers, the system will automatically anticipate massive foot-traffic surges from major public events.