OptiMeal – Meal Assistant

Traditional meal planning tools are rigid and time-consuming, requiring users to decide a week's worth of meals in advance. When daily energy levels fluctuate or schedules change, these rigid plans are abandoned, leading to meal decision fatigue, wasted pantry ingredients, and reliance on unhealthy delivery options.

Our primary persona is the Lifestyle Optimizer — a busy, goal-oriented individual (aged 20–40) seeking a healthy diet with minimal cognitive load. Simulated usability testing highlighted three key needs:

• Time Constraints: Users prefer rapid, low-friction suggestions when tired.
• Quality Confidence: Users need clarity and trust in meal composition.
• Flexibility: Dynamic suggestions outperform static weekly schedules.

OptiMeal acts as a dynamic meal suggestion engine instead of a static planning calendar. Suggestions adapt in real time to three inputs:

• Energy Levels: Low, Standard, or High effort, matching the time available to cook.
• Pantry Availability: Prioritizes recipes using items the user already has.
• System Constraints: The initial scope is restricted to plant-based meals to simplify onboarding and focus testing.

The platform focuses on three main interaction loops:

• Smart Meal Suggestion: User input of current energy level dynamically generates tailored recipes based on preparation complexity.
• Smart Pantry Management: Users interactively select ingredients they already own. The pantry updates in real time, recalculating missing ingredients and highlighting a "Shop Missing Items" call-to-action.
• Real-Time Recipe Pivot: Users can tap "Short on Time?" within any recipe, transforming it instantly into a faster version that preserves similar ingredients.

Initially, OptiMeal was built as a weekly calendar planner where users budgeted time and scheduled a full week. Feedback showed that scheduling added high friction and made users feel guilty when plans failed.

We pivoted to a dynamic recommendation engine. By removing the requirement to commit in advance, we increased overall user flexibility and better aligned the tool with actual, real-world cooking behaviors.