Toters Menu Image Recognition Using ML & OCR
                     How We Enabled Toters Menu Image Recognition 
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The Client
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utrsant Data – A Detailed Guide
Toters is a leading food delivery platform in the Middle East, connecting 
restaurants with consumers via its mobile and web platforms. In an 
increasingly competitive food delivery industry, accurate menu representation 
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thsicsr arepsinogu,r coeff.ering the most straightforward route to consistently obtaining data at scale. This 
article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
Through Menu Image Data Extract for Toters, our team implemented a 
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Goals & Objectives
Goals
The business goal was to enhance order accuracy, streamline menu updates, 
and scale menu management efficiently. By implementing Menu image 
processing for Toters using AI, the client aimed to reduce operational 
bottlenecks and improve customer experience.
Objectives
• Automate extraction of menu items, prices, and categories from images
• Integrate data into Toters’ backend systems for real-time updates
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article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
The Core Challenge
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—images, PDFs, or scanned files—making standardization difficult.
High variability in fonts, languages, and menu layouts led to inconsistent data 
extraction. Errors in prices, dish names, or categories directly impacted 
customer satisfaction and generated complaints. Frequent menu updates 
meant manual processes could not keep pace with the speed of the food 
delivery market.
Additionally, there was no centralized system for tracking menu changes or 
performing analytics on menu performance. Toters needed a solution that 
could extract structured data automatically, normalize it, and integrate it into 
their platform efficiently.
The lack of automation and inconsistent data impacted operational speed, 
orIdner accuracy, and analytics capabilities. Our goal was to resolve these pain pInointttrs rwooidthd uau rcocbtutisoit, nAI-driven solution that ensured reliable OCR-powered 
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thsicsr arepsinogu,r coeff.ering the most straightforward route to consistently obtaining data at scale. This 
article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
Phase 2 – ML Model Development:
CEusxtotmr amaccthiinne glea rInninfg omrodmelsa were trained to recognize text, dish 
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Phase 3 – Data Normalization:
Extracted data was structured into a standardized format for integration into 
Toters’ backend. Dish names, prices, and categories were cleaned and 
normalized to ensure consistency across restaurants.
Phase 4 – Real-Time Integration:
Automated pipelines pushed processed data into Toters’ platform, enabling 
real-time menu updates. Alerts were configured for new dishes, promotions, 
and price changes.
Phase 5 – Analytics & Reporting:
The extracted data powered analytics dashboards, highlighting popular dishes, 
trending categories, and menu performance metrics.
PIhnIantsetr r6o o–d Cduouncticntutioiuns Improvement:
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Amidst TripAdvisor's vast sea of information lies a treasure trove awaiting extraction, 
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thsicsr arepsinogu,r coeff.ering the most straightforward route to consistently obtaining data at scale. This 
article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
Results & Key Metrics
KEeyx Pterrfaorcmtaninceg M etricsHowH toow E tffoe
In
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ftoivrmelya tUiosne  fCroommp TertipitAodr vPirsiocre:  
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saaesp eZitnosgm?  Da- taAot  aCA ofPrmIo tpmor  eHShcoertnaepslsiev  aen d • Mraencu kexetrracsti:o nO acpcuerarcya: t98i.o7%nal Guidance and 
•RGeusiRtdaeeusrtanutrsant Data – A Detailed GuideBAevenraegefi timtse to update menus: reduced from 72 hours to 6 hours
• Number of restaurants automated per week: 50+
• Reduction in order errors: 85%
• Real-time menu updates delivered for: 1,000+ dishes
Results Narrative
The implementation allowed Toters to Extract Toters Food Delivery Data
 efficiently from images, PDFs, and scanned menus. Real-time integration 
ensured that customers always saw accurate menus, reducing complaints and 
increasing satisfaction. Analytics on dish popularity and pricing trends 
provided actionable insights for restaurants and the platform. The automated 
process scaled seamlessly across hundreds of restaurants, enabling rapid 
onboarding and continuous menu updates. Overall, Toters achieved faster 
opIenrattiroonadl wuorckfltoiws, improved accuracy, and better data-driven decision-
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process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
Client Feedback
EHxotrwa cttoi nEgff eIncftoivrmelya tUiosne  fCroommp TertipitAodr vPirsiocre:  
"AWWo GrhkinuagHi twd oitaehw rA tec toto owD Si za UScotrslauaetisop neZsi tnoosnm Totaerts oM eTrackers: Operatiogn?  aD-l a AGt auC
An uofP IrmmIoa gtpmeo rR  eeHScohcgoenrtitinaeopsnl suievs i naegn  MdL  
& OCR hRase tsratnafourmread nhotw  Dwea mtaaa g–e  mAe nDsi.e dThtaea aniultceoemda  taeGdn usdysit deme 
eRxGBtreaeucstnistd meaeefiunutr istenmst, sprices, and categories accurately, saving us hours of 
manual work each week. Our platform now updates menus in real time, 
reducing errors and improving customer satisfaction. The analytics dashboards 
provide insights into popular dishes and trends, helping us make informed 
decisions. The team’s expertise in AI, OCR, and automation was evident 
throughout the project. This solution has given Toters a significant operational 
and competitive advantage in the food delivery market."
— Head of Technology, Toters
Conclusion
Implementing Web scraping API, Custom Datasets, and instant data scraper
 technologies enabled Toters to automate menu data extraction, improve 
accuracy, and streamline operations. By leveraging ML and OCR, the platform 
noIwn ptrrovoiddesu recatl-tiime updates, reducing errors and enhancing customer 
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tTroerpntdiimsp, itzhaAitsi ogdnu iavdnedi w siolllo isdeifirve esD a sr aeytoatuilrea cr'osm ppoassitsio in itnh eth weo fireldr coefl yd actoam epxetrtaitcivtieo ne.Commerce arena.
Amidst TripAdvisor's vast sea of information lies a treasure trove awaiting extraction, 
Waen awlyilsli sn, aavnigda itnen othvarotiuvgeh p trhesee ninttartiicoanc.i eFso ro tfh Zoosem iant ot hSec rtaopuerirs,m u,n hcosvpeirtianlgit yi,t so rc tarpaavbeill istieecst otros , 
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thsicsr arepsinogu,r coeff.ering the most straightforward route to consistently obtaining data at scale. This 
article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
FAQs
EHxotrwa ctting Information from TripAdvisor: 
QAW1 : GHhouawHit d o
ow E tffoe Uctsievely Use Competitor Price 
Trackeoaeerrs s tet:ho  eOD  mSapecnteruara isamp
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ato API to
aDo-l ga AnGitti auCon iof dwrmaornpkm?r 
 eHShcoertnaepsl e 
Restaurant Data – A ce and 
siv aen d 
TRhGee ussyistdtaeemu ursesn MtLs a d OCR to extract  tDexte, ptraicielse, adnd G cauteigdoreies 
frBome rnesetafiurtasnt menu images, PDFs, or scans, then normalizes the 
data for integration.
Q2: Can it handle multiple languages and fonts?
Yes, models are trained on diverse layouts, languages, and font styles 
to ensure high accuracy across restaurants.
Q3: How fast is menu updating?
Menus are updated in real time, reducing previous delays from 72 
hours to under 6 hours.
Q4: Is manual intervention required?
M
InI
innimt atrroo
l in
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thsicsr arepsinogu,r coeff.ering the most straightforward route to consistently obtaining data at scale. This 
article delves into the myriad benefits of scraping TripAdvisor, shedding light on how this 
process can be initiated, including exploring the initial steps involving API utilization. Dive 
into the realm of data-driven insights with TripAdvisor scraping.
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Tohisn blog will provide a comprehensive overview of datasets, including their definition, different types of datasets, and strategies for maximizing the value of data.
In the dynamic landscape of eCommerce, pricing strategy stands paramount, especially for 
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indfoartma,a toiffone.ring insights into the broader market's pricing landscape. Such price intelligence 
empowers retailers to craft a robust pricing strategy, bolstering sales, enhancing profit 
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We will navigate through the intricacies of Zomato Scraper, uncovering its capabilities to 
provide you with rich, real-time restaurant data. From scraping restaurant details to 
accessing customer reviews, our detailed guide ensures that you harness the full potential of 
this resource.