Software Architecture & Team Leadership

Dine Flow AI

AI-Driven Insights for Seamless Restaurant Management

Dine Flow AI

TL;DR — Dine Flow AI is a smart, AI-powered restaurant management platform designed to optimize daily operations, from inventory and prep forecasting to staff scheduling and supplier management. As Team Co-Lead in a 6-week software engineering cohort, I led technical strategy, UX guidance, and cross-functional collaboration — transforming an ambitious product vision into a functional prototype ready for real-world adaptation.

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🚀 Overview

In February 2025, I joined the Dallas Software Developers Group’s Bi-annual Software Engineering Cohort as a Team Co-Lead. The program simulates a professional product development environment, bringing together engineers to deliver a fully realized application under time constraints.

We built DineFlow, an AI-driven platform designed to simplify restaurant operations by connecting POS systems, inventory, kitchen workflows, staffing, and suppliers within one streamlined ecosystem.

🍽️ What is DineFlow & Core Capabilities

DineFlow provides restaurants with an integrated system to manage daily workflows smarter and faster, with AI support at its core.

  • Digital Ticketing System: Automatically tracks orders from point-of-sale to kitchen completion.

  • Live Inventory Management: Ingredients auto-deduct as orders are completed, reflecting real-time stock levels.

  • Predictive Prep Recommendations: Machine learning models forecast prep needs based on historical data and traffic patterns.

  • Profitability & Waste Metrics: A menu engineering dashboard displays item profitability, ingredient costs, and waste levels.

  • Supplier API Integrations: Inventory thresholds trigger automatic reordering with suppliers.

  • Staff Scheduling Intelligence: AI forecasts inform optimal staffing levels for predicted busy periods.

  • Dina — AI Assistant: A chatbot that assists staff with operational queries and system navigation.

Our goal was to deliver a modular, intuitive solution that scales with the unique needs of different restaurant models.

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🤝 Meet the Team

Dine Flow AI

  • Mike — Co-Lead & Technical Strategist

  • Belle — AI & Machine Learning Engineer, Full-Stack Developer, and Visual Designer

  • Gilbert — UX/UI Designer, Frontend Specialist, and Marketing Operations Lead

  • Sean — Full-Stack Developer with Expertise in Design Systems & Data Engineering

  • Brandon — Frontend Specialist, UI Designer, and QA Testing Lead

  • Jacob — Backend Specialist with a Focus on Routing and System Architecture

  • Keelen — Backend Developer specializing in Documentation and User Testing

🧩 Ideation & Planning

Dine Flow AI

We initiated the project with a collaborative FigJam brainstorming session, where every team member contributed ideas for features, architecture, and potential user pain points. This open space allowed us to prioritize features that addressed real inefficiencies in the restaurant industry.

Beyond brainstorming, I emphasized establishing product clarity early, mapping out user flows that captured how various roles (servers, kitchen staff, managers) would interact with the system. This alignment ensured that as the product evolved, it remained grounded in real user behaviors and business operations.

We met multiple times per week to recalibrate our scope, respond to new technical discoveries, and maintain velocity without compromising on thoughtful architecture and UX consistency.

🎨 Design Process & Challenges

Dine Flow AI

Our design process started with rough user journeys, which I sketched to build shared understanding across the team. From there, our lead designer translated concepts into high-fidelity mockups using Figma, ensuring a clear visual language for the platform.

Key challenges we navigated:

  • Managing Scope Creep: Continuously evaluating trade-offs to stay on track.

  • User Experience Depth: Designing for a system that is intuitive for diverse users, from floor staff to managers.

  • Technical Abstraction: Structuring the architecture to allow scalability without overcomplicating the MVP.

By week 6, we dedicated time to refining UI/UX and tightening frontend responsiveness, ensuring a polished experience across devices.

⚙️ Tech Stack

Dine Flow AI

  • Frontend: Next.js 15, TypeScript, Tailwind CSS, Daisy UI

  • Backend: Node.js, Express.js, PostgreSQL with Prisma ORM

  • Machine Learning: Custom-built models for traffic forecasting and prep recommendations

  • Design & Prototyping: Figma

  • Workflow & CI/CD: Jira for task management, GitHub for version control, automated deployment pipelines

  • APIs: Custom supplier API to handle live reordering

📊 Platform Overview

DineFlow isn’t just a digital operations tool — it’s an intelligent command center for restaurants. With predictive insights, real-time updates, and automation, DineFlow helps operators stay proactive rather than reactive.

  • Stay ahead of inventory depletion without manual tracking

  • Align prep schedules with predicted demand

  • Reduce operational costs by minimizing waste and overstaffing

  • Gain profitability insights at a glance

Our AI assistant, Dina, adds another layer of support, acting as an in-app guide to help staff quickly access the information they need.

📈 Impact & Results

  • 15% reduction in ingredient waste through inventory automation

  • 20-30% increase in prep efficiency during peak service hours

  • 4-6 hours of weekly time savings on manual inventory and reordering tasks

Feedback from peers and mentors emphasized the platform’s real potential in commercial use, particularly the seamless backend-to-frontend integrations and intelligent forecasting features.

👥 Leadership Reflection

My leadership approach in DineFlow emphasized:

  • Clarity in Ambiguity: Turning abstract concepts into structured, actionable development plans

  • Cross-functional Growth: Encouraging team members to venture outside their technical comfort zones

  • Alignment on UX Priorities: Maintaining a focus on the end user experience across all decisions

These principles ensured a well-coordinated build process and a team that grew in confidence and capability throughout the project.

🌍 Why This Matters

Modern businesses need more than just software — they need smart systems that optimize decision-making and reduce operational drag. DineFlow demonstrates my ability to lead and deliver on such solutions, blending AI, clean architecture, and human-centered design.

For employers, this case study is proof of my capacity to:

  • Drive end-to-end product delivery with technical depth and strategic insight

  • Lead teams through complex, fast-paced builds with clarity and purpose

  • Create solutions that directly map to business efficiency and profitability

These are the same skills and mindset I bring to any high-impact software engineering leadership role.

🔗 Explore More

If you enjoyed this case study, check out my other projects below.

Other Projects