The Client Project
Black Box Intelligence is a leading data analytics provider for the U.S. restaurant industry. They needed to unify and modernize their data infrastructure to support cross-product analytics.
Requirements
They needed to simplify legacy systems, unify fragmented data sources, and enable scalable ingestion of large datasets to reduce technical debt while building a foundation for future AI and analytics features.
Migrate Legacy User Creation to Modern APIs
Unify Multiple Product Dashboards into One View
Build a Performance Intelligence System Connecting Guest & Financial Data
Enable Universal Data Import for Reviews, Locations, and Files
Improve Maintainability Across Backend Services
Reduce Infrastructure and Tooling Costs
Simplify Developer Experience with GitHub and DevOps Enhancements
Our Implemented Service
ClickIT supported the internal engineering team in modernizing the platform architecture, building a performance intelligence product that connects multiple datasets into a unified dashboard.
- Migrated legacy Azure Functions (C#) for user creation into Koa.js APIs using TypeScript for easier maintenance
- Unified GI, FI, and WI data into a Performance Intelligence dashboard, allowing users to correlate guest reviews with financial performance metrics
- Built a universal data import interface capable of ingesting restaurant reviews, locations, and third-party data via email or SFTP
- Improved infrastructure efficiency by planning migration of Azure Functions to AWS Lambda.
- Enhanced monitoring & DevOps practices using Datadog, Docker, and Tekton pipelines
- Contributed to cost optimization by phasing out SQL Server and reducing reliance on costly Azure services
- Streamlined developer workflow by initiating a migration from Azure Repos to GitHub for better integrations and DX
Our Tech Stack
VueJS
JavaScript
Node JS
TypeScript
Mongo DB
Snowflake
AWS EKS
Azure
AWS
Datadog
Docker
RabbitMQ
Tekton
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The Results
The collaboration between ClickIT and Black Box Intelligence resulted in major improvements across platform performance, development workflows, and cost efficiency.
- Reduced long-term infrastructure and licensing costs
- Accelerated delivery timelines with improved engineering velocity
- Improved developer experience and system maintainability
The new infrastructure allows for faster feature delivery, better insights across their products, and a stronger foundation for future AI and analytics initiatives.
