Designing with intelligence
Designing with intelligence
how we made HungerBox smarter every day
how we made HungerBox smarter every day
The Brief
The Brief
Using AI not as a gimmick, but as an invisible layer of intelligence that transformed how India’s largest cafeterias operate.
Using AI not as a gimmick, but as an invisible layer of intelligence that transformed how India’s largest cafeterias operate.
The Challenge
The Challenge
Simplify a high-volume ecosystem (6 lakh+ daily orders) where every stakeholder was drowning in guesswork, delays, and decision fatigue.
Simplify a high-volume ecosystem (6 lakh+ daily orders) where every stakeholder was drowning in guesswork, delays, and decision fatigue.
The Impact
The Impact
Increasing repeat orders by 22%
Boosting compliance by 21%
Reducing support tickets by 35%.
Improved app rating 2.3 to 4.2
Increasing repeat orders by 22%
Boosting compliance by 21%
Reducing support tickets by 35%.
Improved app rating 2.3 to 4.2
From Orders
to Overload
From Orders
to Overload
At HungerBox, scale was our reality: 6 lakh+ orders every day, across hundreds of cafeterias. On paper, we were thriving. In practice, the cracks showed:
Users drowning in endless menus, repeating the same orders, never discovering better options.
Admins chasing yesterday’s spreadsheets, always reactive, never proactive.
Vendors cooking blind - prepping too much of one dish, not enough of another.
Ops teams buried in checklists and audits that nobody trusted.
That’s when we turned to AI - not as hype, but as a design weapon to bring clarity, personalization, and velocity to the entire system.
At HungerBox, scale was our reality: 6 lakh+ orders every day, across hundreds of cafeterias. On paper, we were thriving. In practice, the cracks showed:
Users drowning in endless menus, repeating the same orders, never discovering better options.
Admins chasing yesterday’s spreadsheets, always reactive, never proactive.
Vendors cooking blind - prepping too much of one dish, not enough of another.
Ops teams buried in checklists and audits that nobody trusted.
That’s when we turned to AI - not as hype, but as a design weapon to bring clarity, personalization, and velocity to the entire system.
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Finding the gaps: Friction we could Fix
Finding the gaps: Friction we could Fix
We didn’t drop AI blindly. We studied the pain. We mapped the mess.
Methodologies Used:
Ethnographic shadowing across 6 cafeterias
Feedback sentiment mining from 12k+ app reviews
Support ticket tagging and clustering
Funnel drop-off heatmaps via Mixpanel
1:1 interviews with vendors, admins, and regular users
We found:
Users frustrated by irrelevant menus and blind ordering
Admins reactive, not proactive - always waiting on insights
Ops struggling with low compliance and no diagnostics
Vendors flying blind on what’s selling and why
We didn’t need more features. We needed
intelligence woven into every interaction.
We didn’t drop AI blindly. We studied the pain. We mapped the mess.
Methodologies Used:
Ethnographic shadowing across 6 cafeterias
Feedback sentiment mining from 12k+ app reviews
Support ticket tagging and clustering
Funnel drop-off heatmaps via Mixpanel
1:1 interviews with vendors, admins, and regular users
We found:
Users frustrated by irrelevant menus and blind ordering
Admins reactive, not proactive - always waiting on insights
Ops struggling with low compliance and no diagnostics
Vendors flying blind on what’s selling and why
We didn’t need more features. We needed
intelligence woven into every interaction.
That's when we asked ourselves:
That's when we asked ourselves:
What if HungerBox could think?
What if HungerBox could think?
Smarter
User Journeys
Smarter
User Journeys
AI meal recommendations
Built a custom engine that uses order patterns, cafeteria menu cycles, and time-of-day data to suggest meals, sides, and combos. → Reduced cognitive load and increased add-on sales
A camera that knew your food
Used AI to scan user-uploaded food images, identify dishes, and generate macro profiles. Integrated nudges and goal tracking into the ordering experience.
Image classification model (trained in-house)
Nutrition mapping via standardized FSSAI tables
Feedback Routing AI
We built a logic engine to classify feedback based on vendor, item, time slot, and sentiment.
Reduced routing errors by 92%
Closed-loop feedback time dropped from 3 days to 4 hours
AI meal recommendations
Built a custom engine that uses order patterns, cafeteria menu cycles, and time-of-day data to suggest meals, sides, and combos. → Reduced cognitive load and increased add-on sales
A camera that knew your food
Used AI to scan user-uploaded food images, identify dishes, and generate macro profiles. Integrated nudges and goal tracking into the ordering experience.
Image classification model (trained in-house)
Nutrition mapping via standardized FSSAI tables
Feedback Routing AI
We built a logic engine to classify feedback based on vendor, item, time slot, and sentiment.
Reduced routing errors by 92%
Closed-loop feedback time dropped from 3 days to 4 hours
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Smarter
Operations:
Wings App
Smarter Operations:
Wings App
Checklist AI Validation
Ops managers uploaded kitchen and hygiene checklists. We layered AI to validate completion with image proof and anomaly detection.
Flagged recurring misses
Scored compliance weekly per location
Response Analysis Dashboard
AI-generated insights helped cluster issues and suggest targeted interventions for each cafeteria.
The Impact:
Compliance improved by 21%
Reduced field audit costs by 40%
Checklist AI Validation
Ops managers uploaded kitchen and hygiene checklists. We layered AI to validate completion with image proof and anomaly detection.
Flagged recurring misses
Scored compliance weekly per location
Response Analysis Dashboard
AI-generated insights helped cluster issues and suggest targeted interventions for each cafeteria.
The Impact:
Compliance improved by 21%
Reduced field audit costs by 40%
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Smarter
Admins
Smarter Admins
Café Intelligence Console
An AI-powered module where admins ask plain questions and get live data:
“What’s my least busy hour this week?”
“Which vendor’s NPS dropped?”
“What feedback themes are trending?”
Built as a natural-language prompt engine + chart generator
The Impact:
Reports generated 8x faster.
Admin logins went up by 37%
Café Intelligence Console
An AI-powered module where admins ask plain questions and get live data:
“What’s my least busy hour this week?”
“Which vendor’s NPS dropped?”
“What feedback themes are trending?”
Built as a natural-language prompt engine + chart generator
The Impact:
Reports generated 8x faster.
Admin logins went up by 37%
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Smarter
Vendors
Smarter Vendors
Sales Forecasting + Menu Intelligence
We provided vendors with demand predictions, dish-level sales trends, and macro suggestions:
“Prepare more dal on Monday”
“Run an offer on low-sell items at 3 PM”
Vendor AI Assistant (Chat)
Conversational UX layered on top of analytics.
The Impact:
Prep errors dropped by 28%
Vendor satisfaction score up +17% over 6 months
For the first time, kitchens weren’t reacting. They were predicting.
Sales Forecasting + Menu Intelligence
We provided vendors with demand predictions, dish-level sales trends, and macro suggestions:
“Prepare more dal on Monday”
“Run an offer on low-sell items at 3 PM”
Vendor AI Assistant (Chat)
Conversational UX layered on top of analytics.
The Impact:
Prep errors dropped by 28%
Vendor satisfaction score up +17% over 6 months
For the first time, kitchens weren’t reacting. They were predicting.
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The Process:
Designing AI people could trust
The Process:
Designing AI people
could trust
AI is powerful, but only if people believe in it. We followed three principles:
Progressive Disclosure → start simple, reveal complexity on demand.
Explainability → show why a dish was recommended, why an alert was flagged.
Human Override → let people correct AI when needed.
This wasn’t black-box magic. It was intelligence designed for partnership.
AI is powerful, but only if people believe in it. We followed three principles:
Progressive Disclosure → start simple, reveal complexity on demand.
Explainability → show why a dish was recommended, why an alert was flagged.
Human Override → let people correct AI when needed.
This wasn’t black-box magic. It was intelligence designed for partnership.
The Results:
Smarter Everyday
The Results:
Smarter Everyday
App rating soared: 2.3 → 4.2
+13% higher order value from recommendations
Repeat orders up 22%
Refund tickets down 35%
Compliance scores up 21%
Vendors reported greater confidence and less waste
App rating soared: 2.3 → 4.2
+13% higher order value from recommendations
Repeat orders up 22%
Refund tickets down 35%
Compliance scores up 21%
Vendors reported greater confidence and less waste
What we built wasn't flashy AI, It was
What we built wasn't flashy AI, It was
Confidence at Scale
Confidence at Scale
Reflection:
Invisible yet Transformative
Reflection:
Invisible yet Transformative
The magic of this project wasn’t the AI models. It was making them invisible.
For users, it felt like the app finally understood them.
For admins, it felt like decisions made themselves.
For vendors, it felt like the kitchen was suddenly smarter.
What we built wasn’t flashy AI. It was confidence at scale.
For me, this was the moment design became more than pixels, it became about shaping intelligence into something people could trust, without even realizing it.
The magic of this project wasn’t the AI models. It was making them invisible.
For users, it felt like the app finally understood them.
For admins, it felt like decisions made themselves.
For vendors, it felt like the kitchen was suddenly smarter.
What we built wasn’t flashy AI. It was confidence at scale.
For me, this was the moment design became more than pixels, it became about shaping intelligence into something people could trust, without even realizing it.
thank you!
keep exploring
thank you!
keep exploring
Bringing ideas
to life,
one product
at a time
Made with 🔥
Bringing ideas to life,
one product at a time
Made with 🔥