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Проверенная компания
Услуга
Turning Data into a Growth Engine for a Food Tech Platform
Why Data Matters in Food Tech
In food tech, great food alone isn’t enough – the digital experience is just as necessary. Customers expect apps to load quickly, payments to clear instantly, and delivery updates to arrive in real-time. If the system stumbles, customer trust quickly erodes.
One of our clients, a fast-growing food tech platform, was running into exactly this problem. Their rapid expansion had outpaced the original design of the system. Services were fragmented, data was scattered across multiple systems, and scaling the platform became harder with every new user.
The solution wasn’t just a rebuild. They needed a platform re-architected around data – flexible enough to grow, yet powerful enough to deliver reliable insights.
Re-Architecting the Foundation
To create a system built for scale, we reorganized the platform into 17 independent microservices. Each service – orders, loyalty, payments, delivery, call center, notifications, and more – now operates separately. This isolation ensures that a problem in one area no longer brings down the entire system.
For service-to-service communication, we introduced Dapr, which simplifies connections without adding unnecessary complexity.
Making Data Work Harder
With more than 3 million users, efficient data management was a top priority. Previously, order history, payments, and logs were stored in different places, creating silos.
We introduced a streamlined data model:
• MongoDB for order history
• PostgreSQL for payments, loyalty, and admin data
• Amazon OpenSearch for search, logs, and audits
Additionally, we have added coverage maps that visualize order distribution and shop performance. Instead of raw numbers, managers now see actionable insights.
Cloud and Analytics with AWS
The platform was fully standardized on AWS, simplifying infrastructure and enabling advanced analytics. Data from various services flows into Amazon Redshift, enabling cross-service reporting without additional integrations.
Using Amazon QuickSight, business leaders now access real-time dashboards, reports, and performance tracking. The same data powers personalization features, such as birthday offers and targeted discounts, which automatically boost customer engagement.
Real-Time Reliability
Customer experience improved further with real-time updates. Delivery status changes and payment confirmations are now pushed instantly using AWS Lambda, Amazon SQS/SNS, and WebSockets. This reduced call center inquiries and provided customers with smooth, transparent order tracking.
Security, Monitoring, and Automation
To strengthen security and reliability, we introduced modern monitoring and automation tools:
• Jaeger for tracing system performance and spotting slow queries
• DefectDojo for continuous vulnerability management
• HangFire for scheduling recurring background jobs
These upgrades keep the platform secure, efficient, and always monitored.
Better Experience for Developers and Users
We also streamlined development with a monorepo architecture, making it easier for teams to work across web, mobile, and admin tools.
On the frontend, Next.js with Incremental Static Regeneration improved page speed and reduced the time required for content updates.
On the backend, we rewrote the system in .NET, replacing the previous mix of Python and Go. This not only unified communication between services but also automated workflows that previously depended on spreadsheets.
The Outcome
The rebuilt platform delivered benefits beyond technical fixes:
• Faster updates and greater stability improved the user experience
• Reduced manual effort, freed up teams, and minimized human error
• Smarter analytics enabled data-driven campaigns and strategic decisions
• Lower call center load thanks to instant customer notifications
What was once a fragmented system is now a cohesive, data-driven platform. The company can manage operations more efficiently, personalize customer experiences, and make confident business decisions backed by facts.
Conclusion
By putting data at the core of its platform, the client turned technology from a barrier into a growth engine. The result is not just a more reliable service today, but a foundation strong enough to support future expansion.
In food tech, great food alone isn’t enough – the digital experience is just as necessary. Customers expect apps to load quickly, payments to clear instantly, and delivery updates to arrive in real-time. If the system stumbles, customer trust quickly erodes.
One of our clients, a fast-growing food tech platform, was running into exactly this problem. Their rapid expansion had outpaced the original design of the system. Services were fragmented, data was scattered across multiple systems, and scaling the platform became harder with every new user.
The solution wasn’t just a rebuild. They needed a platform re-architected around data – flexible enough to grow, yet powerful enough to deliver reliable insights.
Re-Architecting the Foundation
To create a system built for scale, we reorganized the platform into 17 independent microservices. Each service – orders, loyalty, payments, delivery, call center, notifications, and more – now operates separately. This isolation ensures that a problem in one area no longer brings down the entire system.
For service-to-service communication, we introduced Dapr, which simplifies connections without adding unnecessary complexity.
Making Data Work Harder
With more than 3 million users, efficient data management was a top priority. Previously, order history, payments, and logs were stored in different places, creating silos.
We introduced a streamlined data model:
• MongoDB for order history
• PostgreSQL for payments, loyalty, and admin data
• Amazon OpenSearch for search, logs, and audits
Additionally, we have added coverage maps that visualize order distribution and shop performance. Instead of raw numbers, managers now see actionable insights.
Cloud and Analytics with AWS
The platform was fully standardized on AWS, simplifying infrastructure and enabling advanced analytics. Data from various services flows into Amazon Redshift, enabling cross-service reporting without additional integrations.
Using Amazon QuickSight, business leaders now access real-time dashboards, reports, and performance tracking. The same data powers personalization features, such as birthday offers and targeted discounts, which automatically boost customer engagement.
Real-Time Reliability
Customer experience improved further with real-time updates. Delivery status changes and payment confirmations are now pushed instantly using AWS Lambda, Amazon SQS/SNS, and WebSockets. This reduced call center inquiries and provided customers with smooth, transparent order tracking.
Security, Monitoring, and Automation
To strengthen security and reliability, we introduced modern monitoring and automation tools:
• Jaeger for tracing system performance and spotting slow queries
• DefectDojo for continuous vulnerability management
• HangFire for scheduling recurring background jobs
These upgrades keep the platform secure, efficient, and always monitored.
Better Experience for Developers and Users
We also streamlined development with a monorepo architecture, making it easier for teams to work across web, mobile, and admin tools.
On the frontend, Next.js with Incremental Static Regeneration improved page speed and reduced the time required for content updates.
On the backend, we rewrote the system in .NET, replacing the previous mix of Python and Go. This not only unified communication between services but also automated workflows that previously depended on spreadsheets.
The Outcome
The rebuilt platform delivered benefits beyond technical fixes:
• Faster updates and greater stability improved the user experience
• Reduced manual effort, freed up teams, and minimized human error
• Smarter analytics enabled data-driven campaigns and strategic decisions
• Lower call center load thanks to instant customer notifications
What was once a fragmented system is now a cohesive, data-driven platform. The company can manage operations more efficiently, personalize customer experiences, and make confident business decisions backed by facts.
Conclusion
By putting data at the core of its platform, the client turned technology from a barrier into a growth engine. The result is not just a more reliable service today, but a foundation strong enough to support future expansion.
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