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Compare APISOFT vs qCloudy

Side-by-side comparison of features, pricing, services, ratings and more.

APISOFT Agency logo

APISOFT

Web Development & Technology Website

APISOFT is a software development and CRM consulting firm founded in 2023 and headquartered in Astana, Kazakhstan. The company builds CRM modules, parsers, widgets, APIs, and e-commerce integrations for internet-based businesses, with clients including LG online store, Leroy Merlin, and Alfa-Bank.

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qCloudy Agency logo

qCloudy

IT Services & Technology Consulting Website

qCloudy is a cloud consulting agency that helps businesses design and optimize cloud infrastructure using DevOps, DataOps, and MLOps practices. Its certified engineers deliver tailored solutions for cloud migration, automation, hybrid cloud, and CI/CD.

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Feature Comparison

Attribute APISOFT qCloudy
Category Web Development & Technology IT Services & Technology Consulting
Rating - -
Location Astana, Kazakhstan Almaty, Kazakhstan
Services
  • Software Development
  • CRM Consulting
  • CRM Module Development
  • Parser Development
  • Widget Development
  • API Development
  • E-commerce Integration
  • Cloud Consulting
  • Cloud Migration
  • Automation
  • Hybrid Cloud Solutions
  • CI/CD
  • DevOps
  • DataOps
  • MLOps
  • Software Development
  • CRM Consulting
  • CRM Module Development
  • Parser Development
  • Widget Development
  • API Development
  • E-commerce Integration
  • Cloud Consulting
  • Cloud Migration
  • Automation
  • Hybrid Cloud Solutions
  • CI/CD
  • DevOps
  • DataOps
  • MLOps
Industries
E-commerce Retail Banking and Finance
-
Pros
  • Deep expertise in CRM modules, parsers, widgets, APIs, and e-commerce integrations
  • Seven core principles emphasizing thorough analysis, honest communication, and strict deadline adherence
  • Provides comprehensive post-project documentation and ongoing support
  • Certified engineers design tailored cloud solutions
  • Customer-centric approach focused on scalability and cost reduction
  • Experience across DevOps, DataOps, and MLOps practices
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