Projects using AngularJS in Riga
Projects using AngularJS in Riga
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Jonathan DeLaigle
Scalable Shipping & Fulfillment Platform
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3
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Matias Camiletti
eWire | Social News Network APP
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12
1
Dishant | Ex - Instantly, Copilot, Loti
Pro
From Messy to Mesmerizing- Framer Migration and Redesign
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5
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Viktor Gavrilovic
Pro
Sudoku: 200k+ monthly visitors
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29
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Mrs. Pinki
Pro
High-Performance Real Estate with PHP, Angular, Vue.js
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7
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Jayesh MSP
Pro
FESTPASS Website Development
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Kamran Hameed
OnlineDoc - Global Doctor's Collaboration Platform
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3
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Nathan Minnick
Pro
Medical Lab QA software CarePoint Solutions focuses on improving diagnostic accuracy and reducing medical errors. I contributed to the development and maintenance of a SaaS platform featuring an Angular-based frontend and a Drupal/PHP backend. The backend was integrated with MySQL and MongoDB for data handling. Skills AngularJS JasperReports Drupal PHP MongoDB
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Cleave Masereka
Pro
Fintech Platform Software Development
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Ali Shah Lakhani
PETRONAS: 70% reduction in UI/UX Clutter | Design + Development
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34
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Alexander Burton
Pro
Pillowfort.social | American Blogging & Social Networking Site
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1
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Ben Tyler
Denver Metro Water Quality Assessment Tool
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JHON REYNOSO
BHD BANK - Business Mobile Banking
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7
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Gaurav Ahir
dba-cc/Infra-Management-Console
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4
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Pavel Konan
Streamlining Fish Auctions Data through Integration with Custome
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8
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Aravindhkrishnan Prakash
Project: AI-Driven Billing Intelligence System (BNY) Company: Bank of New York (Product-based Company) Built an end-to-end AI-powered Billing Intelligence System for BNY combining ML anomaly detection, dynamic billing-rule validation, full-stack dashboards, and a conversational AI chatbot. Developed ML models to detect billing anomalies, sudden spikes/drops, and unusual usage patterns. Integrated AI agents that validate client billing data against dynamic business rules. Built a full-stack dashboard (Angular+ Flask) for monitoring metrics and reviewing anomalies. Implemented an AI chatbot capable of answering client-specific billing questions, explaining detected anomalies, and summarizing key insights from billing data. Deployed backend APIs and ML services to Google App Engine for scalable enterprise use.
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