Build an AI-Powered SaaS Platform for Restaurant Menu Research & Creation

Project Overview

I’m the founder of GapGastro.com, a business focused on helping food and beverage businesses create unique, competitive, and profitable menus.

I want to transform GapGastro into an AI-powered software platform where restaurant owners, café owners, food truck operators, and other F&B businesses can research, develop, price, and build their entire menus themselves.

The goal is to build a smart platform that does much more than generate recipes. It should help business owners make informed menu decisions using market trends, local competition, pricing, customer preferences, and ingredient costs.

I’m looking for a developer or a small team who can help me build the first working version of this product (MVP), with the potential for long-term collaboration.

How the Platform Should Work

A user signs up, enters their business details, and the platform guides them through a structured menu-development process.

1. Business & Market Research

Ask users about their business type, location, target customers, cuisine, and price range.

Research relevant food trends and emerging consumer preferences.

Analyze local competitors, their menus, pricing, popular offerings, and positioning where reliable data is available.

Identify gaps and opportunities the business could capitalize on.

Provide research-backed recommendations rather than generic AI suggestions.

2. Menu Strategy & Concept Development

Recommend a menu concept based on the business's goals and market.

Identify potential signature dishes and unique selling points.

Suggest categories, menu structure, and the ideal number of items.

Help users differentiate themselves from nearby competitors.

3. AI-Powered Recipe Development

Generate original recipe concepts tailored to the business and its target customers.

Provide ingredient quantities, preparation instructions, portion sizes, and serving suggestions.

Allow users to customize recipes based on cuisine, dietary requirements, equipment, and ingredient availability.

Enable users to refine, regenerate, save, and organize recipes.

4. Pricing & Profitability Analysis

Estimate recipe costs using ingredient quantities and available supplier or user-provided pricing data.

Calculate cost per serving, food-cost percentage, and estimated gross profit.

Recommend selling prices based on costs, target margins, and competitor pricing.

Allow users to update ingredient costs and see how this affects profitability.

5. Complete Menu Builder

Let users select their preferred recipes and organize them into a complete menu.

Provide a centralized dashboard to edit dishes, descriptions, ingredients, prices, and categories.

Identify potential issues such as overlapping dishes, excessive ingredient variety, and weak profitability.

Generate a professional, downloadable menu and a detailed internal recipe and costing report.

6. Saved Projects & User Dashboard

Save menus, recipes, research, and pricing calculations.

Allow users to return and continue working on their projects.

Provide a simple, intuitive dashboard for managing multiple menus.

Build the system with the possibility of subscription plans and paid features in the future.

Important: Research Quality Is the Core Differentiator

I do not want a basic chatbot that simply connects to an AI API and generates random recipes.

The platform must follow a structured research and decision-making workflow. It should distinguish between verified market information, estimated figures, and AI-generated recommendations.

For example, if a restaurant owner enters their location, the system should use available sources to investigate the local competitive landscape, compare menu prices where possible, and identify opportunities before recommending dishes.

The platform should explain why it recommends a particular dish, price, or menu concept.

I understand that some market data may not be publicly available. The developer should propose a practical approach to sourcing, validating, and updating this information rather than promising data that cannot reliably be obtained.

Suggested Technology

I am open to your recommendations, but the proposed solution may involve:

AI APIs and structured prompt/workflow design.

A modern web application with a responsive user interface.

A backend and database for users, recipes, menus, research, and costing.

Web search or suitable data sources for market and competitor research.

Recipe costing and pricing calculation logic.

Secure authentication and a scalable architecture.

Please recommend the most cost-effective and reliable technology stack for the MVP. I am open to both traditional development and AI-assisted development.

Project Scope & Development Approach

I prefer to build this in phases.

Phase 1 — MVP
Build the core user journey: business onboarding, market research, menu recommendations, recipe creation, recipe costing, menu building, and downloadable reports.

Phase 2 — Improvements
Improve research quality, competitor analysis, ingredient and supplier data, menu optimization, and user experience based on testing.

Phase 3 — SaaS Expansion
Introduce subscription billing, advanced analytics, additional integrations, and other premium features.

The initial goal is a functional, testable MVP, not an unnecessarily complicated enterprise platform.

Who Should Apply?

I am particularly interested in freelancers who have experience with one or more of the following:

AI-powered SaaS platforms.

LLM integrations and AI workflows.

Research tools, web search, and data extraction.

Recommendation engines and data-driven applications.

SaaS dashboards, databases, and authentication.

Restaurant technology, food-tech, menu engineering, or recipe applications.

You do not need to have experience in every category. A strong technical approach and the ability to build a reliable MVP are more important.

What to Include in Your Proposal

To help me evaluate your bid, please answer these questions:

Have you built an AI-powered SaaS product or research tool before? Please share relevant examples or demos.

How would you build the research process so that recommendations account for local trends, competitors, menu prices, and profitability?

Which APIs, data sources, and technology stack would you recommend, and why?

What would you include in the first MVP, and what would you leave for later?

What is your estimated timeline and budget for the MVP?

Would you be available for future development if the initial version performs well?

Please provide a clear breakdown of the proposed features, deliverables, and costs.

Long-Term Opportunity

This is intended to become a specialized SaaS product for the food and beverage industry, not a one-off website.

I am looking for someone who can contribute ideas, challenge impractical assumptions, and help build a product that delivers real value to restaurant owners.

If the MVP is successful, there is potential for continued development and a long-term working relationship.

Please start your proposal with the words “MENU INTELLIGENCE” so I know you have read the project description carefully.

I look forward to reviewing your approach, relevant work, and proposal.