PriceWise - A grocery prices database built by and for budget-conscious communities
NYC Open Data Week – March 25, 2026
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Speaker: Shiva Muthiah - Designer and Developer;
Moderator: Shakil Assi - Mayor’s Office for Economic Opportunity
Introduction to PriceWise and Food Pricing Transparency
Shiva Muthiah introduced PriceWise as a community-built grocery price database designed to help budget-conscious New Yorkers make more informed food purchasing decisions. He described himself as a designer, developer, and photographer interested in making data more legible, accessible, and actionable, particularly for nonprofits and public-interest projects.
Muthiah explained that PriceWise emerged from his own personal experience after losing his job in 2025. He and his partner found it difficult to compare grocery prices across stores and determine where to shop most efficiently. This led him to initially build a private comparison tool, which later evolved into a broader community-oriented project.
He framed PriceWise as a response to growing food insecurity in New York City, citing several pressures:
Roughly one in four New Yorkers live in poverty
Many households spend up to 70% of income on food
Food costs have risen by over 50% during the past decade
SNAP benefits increasingly fail to fully bridge affordability gaps
Muthiah argued that food affordability problems are intensified by opaque pricing systems and algorithmic pricing practices used by large retailers.
Algorithmic Pricing and Information Asymmetry
A major theme of the presentation involved the lack of transparency in modern grocery pricing systems.
Muthiah discussed how large retailers increasingly use:
Dynamic pricing systems
E-Ink shelf labels
Data brokers
Machine learning models
Loyalty program data
Consumer browsing histories
to optimize prices in real time.
He explained that retailers can now rapidly adjust prices across entire stores within seconds and combine external data sources with customer purchasing behavior to personalize or optimize pricing strategies.
This creates what he described as a major “information asymmetry” between retailers and consumers. In theory, efficient markets assume consumers make rational choices using perfect information, but in reality consumers face:
Limited information
Limited time
Limited financial flexibility
PriceWise was designed specifically to address the information gap by creating a bottom-up, community-generated grocery pricing database.
Muthiah contrasted these opaque systems with the Park Slope Food Coop, which openly discloses that it applies a 25% markup over wholesale prices, unlike many retailers that may apply markups between 30% and 80%.
Discussion with Participants on Desired Grocery Data
Muthiah paused to ask attendees how they would use open grocery pricing data if it were widely available citywide. Participants suggested many possible uses and related datasets, including:
Comparing store prices more effectively
Understanding which stores accept SNAP/EBT
Identifying local versus imported products
Supporting small “mom-and-pop” stores
Understanding food transportation distances
Tracking tariff impacts
Finding stores with specific community features
The discussion reinforced Muthiah’s argument that consumers currently lack accessible, consolidated information needed to make informed food purchasing decisions.
Demonstration of the PriceWise Web Application
Muthiah then demonstrated the live PriceWise web application, available at “pricewise.nyc.” He emphasized that the platform is:
Free to use
Browser-based
Accessible without downloading an app
Anonymous, requiring no account creation
He demonstrated searching for grocery items while planning a Thai curry meal. Using mushrooms and coconut milk as examples, he showed how PriceWise allows users to:
View price ranges for products
Compare average and median prices
Identify the cheapest nearby stores
Evaluate whether a current in-store price is reasonable
The app displayed item prices connected to specific stores and neighborhoods, enabling users to make decisions about where to shop.
Muthiah also previewed future features that were still under development, including:
Neighborhood-level filtering
Personalized shopping lists
Budget estimation tools
Location-aware price comparisons
Community-Generated Receipt Data Collection
Muthiah explained that all pricing data inside PriceWise comes from community-contributed receipt photographs. Users simply photograph receipts with their phones and upload them to the platform.
He demonstrated the upload workflow:
Photograph a receipt
Select the store
Upload the receipt
Allow the system to process the image automatically
The backend processing pipeline then:
Extracts text using OCR
Structures receipt data using Gemini large language models
Normalizes inconsistent item names
Connects products with store and neighborhood datasets
Adds the structured information into the searchable database
Muthiah emphasized that receipt normalization is especially important because stores use inconsistent naming conventions for identical products. Examples included differing descriptions for the same milk products or abbreviated item names on receipts.
The platform then presents extracted data alongside receipt images so users can verify or manually correct the OCR results before finalizing uploads.
Technical Architecture and Open Data Sources
Muthiah explained that PriceWise uses relatively lightweight and accessible open web technologies, including:
HTML
CSS
JavaScript
Flask
SQLite
He credited NYC Open Data for supplying key datasets used by the application, particularly:
Grocery store location datasets
Neighborhood datasets
GeoSearch APIs for mapping stores to neighborhoods
Later in the Q&A, he clarified that the project also relies heavily on the USDA Retail Food Stores dataset, which provides statewide grocery store information.
“The Price Is Wise” Interactive Quiz
Muthiah introduced a small experimental game called “The Price Is Wise,” designed to test participants’ intuition about grocery prices.
Participants answered questions involving:
Matching food items with prices
Comparing relative grocery costs
Guessing unusually expensive items
One question revealed that milk — specifically a multi-pack milk product — was the single most expensive purchase recorded in the PriceWise database at that time, surprising both presenters and participants.
The game also illustrated how difficult it can be for consumers to estimate fair grocery prices accurately.
Short-Term Challenges: Bootstrapping and Messy Data
Muthiah described several major short-term challenges facing the project.
The first was a classic “bootstrapping” problem:
The platform needs enough data to become useful
People are less likely to contribute data if the database remains sparse
To address this, Muthiah has been conducting grassroots outreach through:
Open Data Week events
Friends and neighbors
Potential future outreach at farmers markets
Community organizations
Mutual aid groups
Local elected officials
Another major challenge involves messy receipt data. He explained that receipts vary dramatically in:
Layout
Formatting
Naming conventions
Quantity notation
Pricing structures
As a result, the system requires both automated normalization techniques and manual curation strategies to unify comparable products.
Long-Term Challenges: AI, Ethics, and Sustainability
Muthiah devoted substantial time to broader long-term concerns surrounding AI systems, transparency, and sustainability.
He noted that AI systems are inherently non-deterministic, meaning identical receipts can sometimes produce slightly different extraction results.
He also raised ethical concerns involving:
Intellectual property issues in AI training
Energy consumption
Dependence on large commercial AI systems
Muthiah suggested that future versions of PriceWise might eventually transition toward smaller, more specialized models trained specifically for receipt analysis.
Another concern involved ownership and governance of community-created data. He emphasized that because the database is built collectively by users, safeguards are needed to prevent exploitation or privatization of community-generated pricing data.
Muthiah also discussed the importance of transparency in both:
The software itself
The decision-making logic embedded within the system
He noted that open-sourcing code alone does not guarantee accessibility or understanding for ordinary users.
Finally, he discussed sustainability challenges, including:
Hosting costs
Domain expenses
AI API costs
Time investment
At the time of the presentation, hosting costs were approximately $12–20 per month, while Gemini API usage had totaled roughly $11 after processing hundreds of receipts. However, he emphasized that the project represented hundreds of unpaid hours of personal labor.
Comparison with Similar Grocery Data Projects
Muthiah reviewed several other grocery-pricing and food-data initiatives for comparison.
These included:
Savvy Prices
Basket
Fetch
Open Prices
Open Food Facts
Matpriskollen (Sweden)
He explained that many competing systems focus primarily on scraping data from major retail chains, which excludes small independent grocery stores that are common throughout New York City.
The Swedish platform Matpriskollen particularly inspired him because Swedish regulators encouraged large retailers to share pricing data more openly during periods of concern over food inflation. Muthiah suggested that a similar future could potentially emerge in the United States.
Future Roadmap for PriceWise
Muthiah outlined a three-phase vision for PriceWise.
Phase One:
Building core infrastructure
Receipt ingestion
Data normalization
Database creation
Phase Two:
Personalized shopping lists
Neighborhood-specific recommendations
Budget forecasting
More actionable user tools
Phase Three:
Advanced visualizations
Geographic price comparisons
Historical price tracking
SMS-based access
EBT-focused accessibility features
He emphasized that future development would require deeper collaboration with food policy experts, community organizations, and researchers working on food access and food equity issues.
Questions About Store Distance, Barcodes, and Dynamic Pricing
During the Q&A session, participants asked numerous technical and usability questions.
Muthiah confirmed that future versions could include distance-based shopping optimization, allowing users to identify the cheapest prices within a specified walking radius.
Questions also addressed:
Handling extremely long receipts
Simplifying the interface for less technical users
Showing upload dates for pricing data
Expanding the system to other cities such as Boston
Participants proposed using UPC barcodes to standardize products across stores. Muthiah acknowledged this as a promising future direction and noted that Open Food Facts already uses similar barcode-based approaches.
He also acknowledged that the current system does not yet fully account for:
Sale pricing
Temporary discounts
Coupons
Dynamic price fluctuations
These remain active development challenges.
Discussion on Public Policy and Economic Research Applications
Participants suggested that PriceWise could potentially support broader economic research, including price-index calculations used by the Bureau of Labor Statistics.
Muthiah responded that he had studied some inflation-tracking methodologies and was interested in potentially integrating benchmark pricing information, such as Park Slope Food Coop wholesale markup data, into future analyses.
Closing Discussion on Community Outreach and Scaling
Toward the end of the session, Muthiah reflected on future outreach plans and technical scalability.
He explained that the system had already been tested with approximately 3,000–4,000 purchases and was functioning reliably at that scale.
Future outreach plans include:
Farmers market demonstrations
Partnerships with mutual aid organizations
Engagement with community boards
Collaboration with block associations
The session concluded with broader reflections on the importance of making pricing data more legible, transparent, and accessible for ordinary residents navigating rising food costs and increasingly opaque retail systems.
RESOURCES
PriceWise — community-built grocery price database for NYC, presented by Shiva Muthiah (currently in beta)
Shiva Muthiah — designer, developer, and photographer who built PriceWise
Retail Food Stores dataset — NYS open dataset of licensed grocery stores, published by the Department of Agriculture and Markets
NYC GeoSearch API — address-to-neighborhood geocoding service used to map stores to neighborhoods
Open Prices — crowdsourced open database of food prices, part of Open Food Facts
Open Food Facts — open barcode-based food product database referenced for item identification
Matpriskollen — Swedish grocery price comparison service cited as an inspiring model for data-sharing
Savvi — Vancouver-focused grocery price comparison tool
Park Slope Food Coop — Brooklyn cooperative noted for its transparent flat 25% markup on wholesale prices
NYC Open Data — the city’s public data portal, source of the grocery store and neighborhood datasets