A mobile augmented-reality app that helps expectant mothers in urban India make informed food choices — scan any food item and see its nutritional impact overlaid in real time, narrated from the baby's point of view.
Pregnancy in urban India comes with a specific set of nutrition challenges: conditions like anaemia and gestational diabetes are common, nutritional knowledge is inconsistent, and cultural beliefs around food during pregnancy are often more folklore than fact. At the same time, smartphone ownership in urban India is now widespread, which made a mobile intervention genuinely feasible rather than aspirational.
The idea: point a phone's camera at a food item, and instantly see what it means for you and your baby — grounded in WHO maternal nutrition guidelines, not guesswork.
Before designing anything, I sized the market: India's AR sector was projected to reach US$14.07bn by 2027, growing at a 38.29% CAGR, driven by rising smartphone penetration. I then benchmarked four existing nutrition-focused apps — FoodLens, Calorie Mama, ARFood and Red Laser — across their technology, features, differentiators and pricing.
Solid image-recognition tech and calorie tracking (FoodLens, Calorie Mama), real-time label scanning (ARFood, Red Laser).
None were built for pregnancy specifically — no maternal-health framing, no trimester-aware guidance, no cultural tailoring for Indian diets.
A nutrition AR app purpose-built for prenatal health in urban India didn't exist yet — the gap this project targeted directly.
A structured SWOT surfaced real constraints alongside the opportunity: strong differentiation and health impact potential, weighed against genuine adoption risk from device requirements, unfamiliarity with AR, and the challenge of staying culturally and linguistically relevant across India's diversity.
I mapped the full business model — not just the interface — covering key partnerships (healthcare professionals, nutritionists, local food suppliers), a freemium revenue structure with in-app purchases, distribution through major app stores and healthcare-professional referral, and cost drivers spanning development, content curation and partnerships. I also considered second-order impact: the app's potential contribution to maternal health outcomes at a population level, and its resource footprint (device energy use, data privacy obligations around sensitive health information).
The target audience is working professional women, 25–35, in urban India — tech-savvy, time-poor, and anxious to get pregnancy right. I built two personas from this research to keep design decisions anchored to real motivations rather than assumptions.
Neha
"It's been hard for us to get pregnant and I am so worried I will lose this baby."
Executive assistant in New Delhi. Previous miscarriage makes her acutely risk-averse; she wants a trusted source of guidance rather than one more thing to Google.
Amrita
"I want to enjoy a healthy pregnancy experience and hope my baby is born healthy too."
Accountant in Mumbai, first pregnancy. Overwhelmed by conflicting myths about what's safe to eat, and unsure which advice to trust.
Both personas shared the same underlying tension: motivated to do the right thing nutritionally, but short on reliable, fast answers at the point of decision — usually standing in a supermarket aisle.
I mapped the core interaction as a use-case flow before designing any screens: a user completes a short one-time profile (due date, date of birth, weight, height), which the app uses to calculate trimester, BMI and daily caloric needs. From there, she simply scans a food item, and the app overlays dietary guidance in real time.
Core use-case flow: from one-time profile setup to real-time AR nutrition overlay.
Design started with hand-drawn sketches to keep early ideas loose, then moved into low-fidelity Adobe XD wireframes once the core interaction felt right. I informally tested these sketches and wireframes with pregnant women and mothers in my personal network before investing in high-fidelity visuals — catching usability issues while they were still cheap to fix.
The brand identity centres on a simple, feminine icon of a woman with a baby bump, paired with a soft pink-and-green colour palette chosen deliberately through a colour-psychology lens: pink for warmth and nurture, green for growth and wellbeing. Sansita Swashed gives the logotype a graceful, human touch, while the clean, modern Urbanist typeface carries the informational content inside the app for maximum readability.
High-fidelity AR overlay concept — colour-coded by information type, narrated from the baby's perspective for emotional engagement.
The working prototype was built in Unity, integrating a 3D baby character (rigged and animated, then modified in Photoshop for cultural fit) that visually "speaks" to the mother through the overlay — a first-person narrative device that made the nutrition data feel personal rather than clinical. Custom C# scripts handled multi-object image recognition, ensured only one overlay showed at a time, and synced sound feedback to transitions and animations.
Technical testing ran across roughly 12 build iterations, working through structured test cases covering app launch, navigation, food recognition, AR overlay accuracy, and audio feedback. Two early rounds surfaced real issues — inconsistent recognition across multiple food items in one scene, and overlay scale/positioning — both resolved before the final build passed every test case.
For user validation, I ran six moderated interviews with pregnant women and mothers, following informed-consent and privacy protocols, then thematically analysed the transcripts across five lenses: first impressions, appeal, engagement, effectiveness and motivation.
"The fetus addressing the mother takes user engagement a step forward — it plays on the psychology of the mother by adding an emotional element."
— Interview participantColour-coded guidance and the baby's-voice narrative were consistently praised as clear and emotionally engaging; participants said they'd wanted an app like this during their own pregnancies.
A few participants found the baby's dialogue bubble colour easy to confuse with the food-information colour coding, and asked for more concise copy in places.
Multiple participants said certification from a healthcare professional would make them more confident acting on the app's guidance — a clear signal for any future iteration.
This project pushed me to hold UX rigour and emotional design together — the persona and use-case work kept the feature set honest, while the baby's-voice narrative device came directly from understanding how emotionally loaded pregnancy nutrition decisions are. It's also the project that most shaped how I think about validating a concept properly: build cheap, test early, and let real user reactions — not just my own assumptions — decide what ships.
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