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Code Review

Our customer is a leading healthcare service provider in the Canadian market, offering a SaaS-based product used by top medical facilities across the country. They faced issues such as long loading times, search failures, and frequent timeout errors. The client wanted us to analyze and identify the root causes of these problems.

2025-04-10

Industry: Healthcare

Service: Code audit & Review

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Project Details

Our primary responsibility during this engagement was to perform a code review cycle for the existing backend and mobile applications (both iOS and Android).

Code review

Problem

The client faced significant challenges, including:

  • High escalation rates, with around 40 unique escalations per business day. Outdated infrastructure with no disaster recovery, auto-scaling, or CI/CD practices.
  • Long load times, sometimes exceeding 3 minutes, leading to frequent timeouts.
  • Numerous broken flows throughout the application.
  • Lack of common modules, resulting in code reusability issues and repetitive code.
  • Over 5 repositories that had not been reviewed, raising concerns about code quality.

Our Approach

We launched a 10-day code review sprint, during which we reviewed the applications and related repositories, checking code quality. Key findings included:

  • No caching for frequently accessed data.
  • Unoptimized code with insufficient comments.
  • Absence of linting tools and pre-publishing checks.
  • Lack of code reusability.
  • Search results were returned directly from DB tables instead of using an ELK stack or similar practices.
  • Over 250 feedback points per repository.
  • Inadequate infrastructure, with no edge security, disaster recovery, or CI/CD setup.
  • We provided solutions for these issues and were awarded the project to implement the necessary changes.

Benefits

Post-implementation, the changes resulted in:

  • A reduction to 3 unique escalations per day, mainly for functional tasks. Significantly improved load times due to the implementation of the ELK stack and caching.
  • Reduced loading times through multithreading, allowing components to load in the background.
  • Adoption of best infrastructure practices, including CI/CD and disaster recovery, to prevent future setbacks.
  • By addressing these issues, we enhanced the application’s performance and reliability, ensuring a better user experience.

Meet the Experts Behind This Project

Every successful software transformation is powered by experienced engineers, architects, designers, and AI specialists. Connect with the experts who have delivered scalable digital solutions across healthcare, fintech, retail, manufacturing, education, and other enterprise industries.

GK

G. Kaur

Senior Data Scientist | 4 Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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Python
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PyTorch
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MLOps
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Forecasting
RS

R. Sharma

Senior Solution Architect | 4+ Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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AWS
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Cloud Architecture
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Microservices
PM

P. Mehta

Lead AI & Data Engineer | 2+ Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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AWS
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Generative AI
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ML
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Python
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