SaaS Testing Services

If you have an in-house QA team but face challenges in recruiting new staff or require specific skills (such as transitioning to automation testing), you can engage our experts to seamlessly integrate into your team and contribute to your project.

02.

Remote SaaS Testing Team

You can delegate testing of your SaaS solution to us so that your company can concentrate on its key competencies while saving some cost.

03.

Project-Based SaaS Testing

For organizations embarking on the development of a new product, service, or capability, we offer external expertise in quality assurance to complement their existing teams, allowing them to maintain their focus on their primary mission.

04.

SaaS Testing as a Service

This engagement model is suitable if you have clear quality goals and need access to pre-packaged expertise to achieve these goals. Our QA team is at your disposal to fulfill your specific requirements.

05.

Consulting on SaaS Testing

In case you have an in-house QA team but it does not deliver the desired results, we can step in to assess and refine your quality assurance processes. Our time-tested processes have consistently proven their efficiency. We provide comprehensive documentation, auditing, implementation, and cost-effective management of your in-house team.

What you get

Average time saved by implementing our multithreaded test automation

300%

Reduction in your costs by using outsourced software testing

60%

Improvement in time to market for your products and projects

35%

Accelerate development by

30%

Increase test coverage to

95%

Enhancing project quality by

60%

Feel the improvement in

3 days

Reduce bugs up to

87%

Automation faster in parallel by

56x

We serve

Our expertise and resources allow us to provide support tailored to the unique needs of each project, ensuring the delivery of high-quality software that meets your requirements and business objectives.

Industries

Healthcare

FinTech

Real Estate

Cybersecurity

Retail

AdTech

Solutions

Banking Apps

SaaS Solutions

ERP Software

CRM Systems

eCommerce

Technologies

Blockchain

Cloud Computing

Internet of Things

Big Data

Partner with DeviQA: see the difference

Test coverage :

90%

Before

After

2.5 weeks to run regression testing

1 day to run regression testing

7 days to run smoke testing

1 day to run smoke testing

Outdated test cases

60% increase in the number of regression tests and relevant test cases

50% test coverage

90% test coverage

Supported localizations were not tested

27 localizations supported by QA engineers

No automation testing

>1500 automated test scenarios created

Test coverage :

97%

Before

After

Existing workflow in Jira didn’t allow to understand how many bugs were left unfixed before the release and their priorities

Adjusted the Jira workflow, integrated TestRail with Jira to be able to see statisticls of the issues per release

The lack of test documentation

Developed necessary test artifacts that adhere to industry standards and are easily maintainable

No Automation test coverage

Added multithreading to run tests in parallel on 10 different threads, which reduced the time of the test run in 7 times

Releases per day:

Before

After

1 huge release every 1-2 months

4-5 releases per day

1 large team with an unclear scope of work

~15 squads each with a straight and clear working plan

0 test cases

200+ e2e test cases for the whole app

1-2 months to release a new feature

2 weeks max to release a new feature

Convoluted and complex process of urgent bug-fix releases

Clear and fast way to release any fix

Test coverage:

90%

Before

After

The architecture of the test suite could not be scaled and was difficult to maintain for a large number of tests

Designed the architecture of the test framework from scratch

Tests couldn’t be integrated with other testing and DevOps tools

Integrated auto tests with Jenkins, TestRail, and Jira to have a complete test ecosystem up and running

Tests took many hours to be completed

Built a test suite that ran auto-tests using 16 threads on multiple machines

Test coverage:

80%

Before

After

Test suite was developed without maintenance and scalability support in mind

We conducted a comprehensive review of the existing test suite, identified areas of improvement and implemented best testing practices

The high number of issues or defects that were present in the software

The number of issues reduced to 25 % after automation was properly implemented

Slow test results and the lack of stable automated tests, leading to hindered deployment capabilities

SoftNAS experienced several benefits, including faster test results and the acquisition of stable automated tests, resulting in improved deployment capabilities

Supported platforms:

Before

After

Developers were responsible for testing, and they executed it chaotically

>90% of the application was covered with test cases

Many bugs were overlooked during regular test runs

100% coverage was ensured for smoke and sanity testing

There was a lack of test documentation

>300 blocker issues were detected

There were many major and critical issues in a production environment

The number of customer support issues was reduced by more than 50%

Parallel threads:

Before

After

Outdated BE autotests

All existing autotests are up-to-date

Only smoke tests were automated on BE

~2800 autotests added

No autotests on FE

>90% of test cases are automated

Manual smoke testing on FE

~99% of smoke tests are automated

Manual release testing

~95% decrease in post-release regression bugs, the implementation of test automation has proven to be highly effective

Test coverage:

90%

Before

After

There was no formal QA process

An efficient and transparent QA process was set up from scratch

There was no test documentation

Well-structured test cases were created to cover the main scenarios

Automation scripts were useless because they didn’t check the required functionality

Following best practices, automation testing utilized independent tests, API-driven data creation, and the Page Object Pattern

Released PWAs:

40+

Before

After

There were no QA engineers, and testing was executed by a product owner and developers

All QA/QC activities are performed by a seasoned QA engineer

All testing activities came down to ad-hoc testing and unit testing

Regression testing, pre-release testing, post-release smoke testing, and smoke testing are regularly executed

100% of the release content is tested using different approaches

150+ Postman test cases were created and integrated into the workflow

Test coverage:

>80%

Before

After

4 days were needed to run regression testing

~2 hours were needed to run regression testing

Regression tests were executed on one device only

5 various devices with different operating systems, screen resolutions, and browsers were used to run regression testing

There were less than 200 automated tests

>1000 automated tests were developed

1 browser was used

4 browsers were supported

Test coverage:

99%

Before

After

There was no formal QA process

Manual story testing and verification was built from scratch

There was a lack of QA resources to test all platforms and product areas

99% of the application was covered with test cases and the smoke and regression checklists

The test documentation was incomplete

A well-structured test plan enabling thorough validation was created

Testing was executed by developers

A fully autonomous QA process was set up where QA engineers were fully responsible for testing

Regression testing run:

Before

After

2 weeks were needed to run regression testing

<1 week is needed to run regression testing

Regression testing was performed only on 2 web devices

>6 various devices with the latest OS versions are used to run regression testing

There were no auto-tests

>150 automated tests have been created

>100 bugs have been reported

3 browsers are supported

2x faster task handling

Test coverage:

>85%

Before

After

Regression testing was not executed

3 hours were needed to complete regression testing

The product contained a lot of bugs and had a bad UX

>300 functional and non-functional bugs were reported

There were no automated tests

350+ automation scenarios were created

Test coverage was low

>85% of the product was covered with automated tests

There were no test cases

350+ test cases were created from scratch

Bugs reported:

>1000

Before

After

The QA process was unstructured and inconsistent

A QA team participates in creating ticket scope for upcoming releases

The previous QA team was not efficient enough

All the required test documentation has been rewritten

The test documentation was incomplete and out of date

>6,000 test cases have been written for a regression test suite for client applications

There were a lot of issues reported by clients

The DeviQA engineers have reduced the number of bugs reported by clients/therapists

Test coverage of the API:

100%

Before

After

A bug-tracking system was not used

280+ regression E2EE cases have been created, which let a team reduce the time of regression testing to 1.5 days

There were no regression checklists

~40% of tests have been automated, and this value is growing

There was poor documentation coverage

100% of the core flow is covered with documentation

The tests were not automated

5+ performance suites have been created

Test coverage :

90%

Before

After

2.5 weeks to run regression testing

1 day to run regression testing

7 days to run smoke testing

1 day to run smoke testing

Outdated test cases

60% increase in the number of regression tests and relevant test cases

50% test coverage

90% test coverage

Supported localizations were not tested

27 localizations supported by QA engineers

No automation testing

>1500 automated test scenarios created

Dev capacity:

+15%

Before

After

Didn’t have a formal QA process

Built smooth and well-working processes

Didn’t make automated testing

Test automation : smoke, API, UI on all supported browsers

Testing was carried out by the devs

Full coverage of the application by test cases

Test coverage :

97%

Before

After

Existing workflow in Jira didn’t allow to understand how many bugs were left unfixed before the release and their priorities

Adjusted the Jira workflow, integrated TestRail with Jira to be able to see statisticls of the issues per release

The lack of test documentation

Developed necessary test artifacts that adhere to industry standards and are easily maintainable

No Automation test coverage

Added multithreading to run tests in parallel on 10 different threads, which reduced the time of the test run in 7 times

Releases per day:

Before

After

1 huge release every 1-2 months

4-5 releases per day

1 large team with an unclear scope of work

~15 squads each with a straight and clear working plan

0 test cases

200+ e2e test cases for the whole app

1-2 months to release a new feature

2 weeks max to release a new feature

Convoluted and complex process of urgent bug-fix releases

Clear and fast way to release any fix

Test coverage:

90%

Before

After

The architecture of the test suite could not be scaled and was difficult to maintain for a large number of tests

Designed the architecture of the test framework from scratch

Tests couldn’t be integrated with other testing and DevOps tools

Integrated auto tests with Jenkins, TestRail, and Jira to have a complete test ecosystem up and running

Tests took many hours to be completed

Built a test suite that ran auto-tests using 16 threads on multiple machines

Test coverage:

80%

Before

After

Test suite was developed without maintenance and scalability support in mind

We conducted a comprehensive review of the existing test suite, identified areas of improvement and implemented best testing practices

The high number of issues or defects that were present in the software

The number of issues reduced to 25 % after automation was properly implemented

Slow test results and the lack of stable automated tests, leading to hindered deployment capabilities

SoftNAS experienced several benefits, including faster test results and the acquisition of stable automated tests, resulting in improved deployment capabilities

Supported platforms:

Before

After

Developers were responsible for testing, and they executed it chaotically

>90% of the application was covered with test cases

Many bugs were overlooked during regular test runs

100% coverage was ensured for smoke and sanity testing

There was a lack of test documentation

>300 blocker issues were detected

There were many major and critical issues in a production environment

The number of customer support issues was reduced by more than 50%

Parallel threads:

Before

After

Outdated BE autotests

All existing autotests are up-to-date

Only smoke tests were automated on BE

~2800 autotests added

No autotests on FE

>90% of test cases are automated

Manual smoke testing on FE

~99% of smoke tests are automated

Manual release testing

~95% decrease in post-release regression bugs, the implementation of test automation has proven to be highly effective

Test coverage:

90%

Before

After

There was no formal QA process

An efficient and transparent QA process was set up from scratch

There was no test documentation

Well-structured test cases were created to cover the main scenarios

Automation scripts were useless because they didn’t check the required functionality

Following best practices, automation testing utilized independent tests, API-driven data creation, and the Page Object Pattern

Released PWAs:

40+

Before

After

There were no QA engineers, and testing was executed by a product owner and developers

All QA/QC activities are performed by a seasoned QA engineer

All testing activities came down to ad-hoc testing and unit testing

Regression testing, pre-release testing, post-release smoke testing, and smoke testing are regularly executed

100% of the release content is tested using different approaches

150+ Postman test cases were created and integrated into the workflow

Test coverage:

>80%

Before

After

4 days were needed to run regression testing

~2 hours were needed to run regression testing

Regression tests were executed on one device only

5 various devices with different operating systems, screen resolutions, and browsers were used to run regression testing

There were less than 200 automated tests

>1000 automated tests were developed

1 browser was used

4 browsers were supported

Test coverage:

99%

Before

After

There was no formal QA process

Manual story testing and verification was built from scratch

There was a lack of QA resources to test all platforms and product areas

99% of the application was covered with test cases and the smoke and regression checklists

The test documentation was incomplete

A well-structured test plan enabling thorough validation was created

Testing was executed by developers

A fully autonomous QA process was set up where QA engineers were fully responsible for testing

Regression testing run:

Before

After

2 weeks were needed to run regression testing

<1 week is needed to run regression testing

Regression testing was performed only on 2 web devices

>6 various devices with the latest OS versions are used to run regression testing

There were no auto-tests

>150 automated tests have been created

>100 bugs have been reported

3 browsers are supported

2x faster task handling

Test coverage:

>85%

Before

After

Regression testing was not executed

3 hours were needed to complete regression testing

The product contained a lot of bugs and had a bad UX

>300 functional and non-functional bugs were reported

There were no automated tests

350+ automation scenarios were created

Test coverage was low

>85% of the product was covered with automated tests

There were no test cases

350+ test cases were created from scratch

Bugs reported:

>1000

Before

After

The QA process was unstructured and inconsistent

A QA team participates in creating ticket scope for upcoming releases

The previous QA team was not efficient enough

All the required test documentation has been rewritten

The test documentation was incomplete and out of date

>6,000 test cases have been written for a regression test suite for client applications

There were a lot of issues reported by clients

The DeviQA engineers have reduced the number of bugs reported by clients/therapists

Test coverage of the API:

100%

Before

After

A bug-tracking system was not used

280+ regression E2EE cases have been created, which let a team reduce the time of regression testing to 1.5 days

There were no regression checklists

~40% of tests have been automated, and this value is growing

There was poor documentation coverage

100% of the core flow is covered with documentation

The tests were not automated

5+ performance suites have been created

Test coverage :

90%

Before

After

2.5 weeks to run regression testing

1 day to run regression testing

7 days to run smoke testing

1 day to run smoke testing

Outdated test cases

60% increase in the number of regression tests and relevant test cases

50% test coverage

90% test coverage

Supported localizations were not tested

27 localizations supported by QA engineers

No automation testing

>1500 automated test scenarios created

Test coverage :

97%

Before

After

Existing workflow in Jira didn’t allow to understand how many bugs were left unfixed before the release and their priorities

Adjusted the Jira workflow, integrated TestRail with Jira to be able to see statisticls of the issues per release

The lack of test documentation

Developed necessary test artifacts that adhere to industry standards and are easily maintainable

No Automation test coverage

Added multithreading to run tests in parallel on 10 different threads, which reduced the time of the test run in 7 times

Releases per day:

Before

After

1 huge release every 1-2 months

4-5 releases per day

1 large team with an unclear scope of work

~15 squads each with a straight and clear working plan

0 test cases

200+ e2e test cases for the whole app

1-2 months to release a new feature

2 weeks max to release a new feature

Convoluted and complex process of urgent bug-fix releases

Clear and fast way to release any fix

Test coverage:

90%

Before

After

The architecture of the test suite could not be scaled and was difficult to maintain for a large number of tests

Designed the architecture of the test framework from scratch

Tests couldn’t be integrated with other testing and DevOps tools

Integrated auto tests with Jenkins, TestRail, and Jira to have a complete test ecosystem up and running

Tests took many hours to be completed

Built a test suite that ran auto-tests using 16 threads on multiple machines

Test coverage:

80%

Before

After

Test suite was developed without maintenance and scalability support in mind

We conducted a comprehensive review of the existing test suite, identified areas of improvement and implemented best testing practices

The high number of issues or defects that were present in the software

The number of issues reduced to 25 % after automation was properly implemented

Slow test results and the lack of stable automated tests, leading to hindered deployment capabilities

SoftNAS experienced several benefits, including faster test results and the acquisition of stable automated tests, resulting in improved deployment capabilities

Supported platforms:

Before

After

Developers were responsible for testing, and they executed it chaotically

>90% of the application was covered with test cases

Many bugs were overlooked during regular test runs

100% coverage was ensured for smoke and sanity testing

There was a lack of test documentation

>300 blocker issues were detected

There were many major and critical issues in a production environment

The number of customer support issues was reduced by more than 50%

Parallel threads:

Before

After

Outdated BE autotests

All existing autotests are up-to-date

Only smoke tests were automated on BE

~2800 autotests added

No autotests on FE

>90% of test cases are automated

Manual smoke testing on FE

~99% of smoke tests are automated

Manual release testing

~95% decrease in post-release regression bugs, the implementation of test automation has proven to be highly effective

Test coverage:

90%

Before

After

There was no formal QA process

An efficient and transparent QA process was set up from scratch

There was no test documentation

Well-structured test cases were created to cover the main scenarios

Automation scripts were useless because they didn’t check the required functionality

Following best practices, automation testing utilized independent tests, API-driven data creation, and the Page Object Pattern

Released PWAs:

40+

Before

After

There were no QA engineers, and testing was executed by a product owner and developers

All QA/QC activities are performed by a seasoned QA engineer

All testing activities came down to ad-hoc testing and unit testing

Regression testing, pre-release testing, post-release smoke testing, and smoke testing are regularly executed

100% of the release content is tested using different approaches

150+ Postman test cases were created and integrated into the workflow

Test coverage:

>80%

Before

After

4 days were needed to run regression testing

~2 hours were needed to run regression testing

Regression tests were executed on one device only

5 various devices with different operating systems, screen resolutions, and browsers were used to run regression testing

There were less than 200 automated tests

>1000 automated tests were developed

1 browser was used

4 browsers were supported

Test coverage:

99%

Before

After

There was no formal QA process

Manual story testing and verification was built from scratch

There was a lack of QA resources to test all platforms and product areas

99% of the application was covered with test cases and the smoke and regression checklists

The test documentation was incomplete

A well-structured test plan enabling thorough validation was created

Testing was executed by developers

A fully autonomous QA process was set up where QA engineers were fully responsible for testing

Regression testing run:

Before

After

2 weeks were needed to run regression testing

<1 week is needed to run regression testing

Regression testing was performed only on 2 web devices

>6 various devices with the latest OS versions are used to run regression testing

There were no auto-tests

>150 automated tests have been created

>100 bugs have been reported

3 browsers are supported

2x faster task handling

Test coverage:

>85%

Before

After

Regression testing was not executed

3 hours were needed to complete regression testing

The product contained a lot of bugs and had a bad UX

>300 functional and non-functional bugs were reported

There were no automated tests

350+ automation scenarios were created

Test coverage was low

>85% of the product was covered with automated tests

There were no test cases

350+ test cases were created from scratch

Bugs reported:

>1000

Before

After

The QA process was unstructured and inconsistent

A QA team participates in creating ticket scope for upcoming releases

The previous QA team was not efficient enough

All the required test documentation has been rewritten

The test documentation was incomplete and out of date

>6,000 test cases have been written for a regression test suite for client applications

There were a lot of issues reported by clients

The DeviQA engineers have reduced the number of bugs reported by clients/therapists

Test coverage of the API:

100%

Before

After

A bug-tracking system was not used

280+ regression E2EE cases have been created, which let a team reduce the time of regression testing to 1.5 days

There were no regression checklists

~40% of tests have been automated, and this value is growing

There was poor documentation coverage

100% of the core flow is covered with documentation

The tests were not automated

5+ performance suites have been created

Deliver Globally

DeviQA's client base encompasses a wide range of businesses, including startups, scale-ups, and publicly listed corporations, from all corners of the globe. Our clients span the United States, the European Union, the UK, Canada, the Middle East, and Australia.

Irrespective of your location on our pale blue dot, we can help you achieve your QA goals no matter how big, small, or unique they are.

Elevate your software quality with our cutting-edge QA solutions.

Don’t let software bugs and performance issues jeopardize your reputation. Surpass your competitors with our specialized data-driven QA solutions that ensure detection and rectification of up to 95% of potential issues. Enter your business email below for a free Proof of Concept to start enhancing your software reliability today.

Here’s what people are saying about DeviQA

Testing for Diabetes Care Firm

Improving testing process efficiency and remaining mindful of the client’s requirements for the project, DeviQA has been an impressive partner. The firm’s project managers have kept the engagement moving smoothly and have made sure the team is available despite working in a different time zone.

Dale Vosburgh

Director, Diabetes Care Firm

Application Testing for Audio Editing Platform

The engagement met the expectations of the internal team, resulting in an easy to maintain testing framework. DeviQA establishes a smooth workflow through consistent communication. The team leverages their technical expertise and experience to produce quality results.

Ulf Schwekendiek

Lead Engineer, Descript

SaaS System Testing for FinTech Startup

Through DeviQA’s involvement, the high-quality product has performed reliably and attracted positive customer feedback. The team’s commitment to excellence, consistent availability, and reasonable price point continue to drive success.

Raanan Tauber

QA Manager, Tipalti

Automated Testing for Sales Learning Platform

Having DeviQA on board has resulted in finding more defects before deploying features to customers, boosting the end product’s overall quality. Their team is not only supportive but also easy to scale as needed. Efficient communication and punctuality are some highlights of their work.

Brad DerManouelian

Senior QA Manager, Sales Learning Platform

Enhanced Testing Environment for BI and Big Data Solutions Firm

DeviQA developed over 300 test cases in a month and a half, which led to a 70% coverage of the business’ solution and a 45% decrease in its defect rate. Furthermore, the team’s timely services allowed them to implement swinging tests alongside the addition of new pieces of functionality.

Brian Huddleston

Former VP of Development

QA, Automation, DevOps & TechOps Support for QC & QA Co

DeviQA has demonstrated to be a highly skilled consultant, as they’ve achieved 95% of the client’s quarterly objectives, as well as sprint goals every two weeks. DeviQA’s consultants are very collaborative and open to feedback. Moreover, their communication and availability are impressive.

Alex Ohoussou

Head of QA & TechOPs, QIMA

QA Testing for Secure Solutions Company

Their independent and accountable team is a significant upgrade compared to experiences with other vendors. DeviQA excels at being punctual, solving problems, communicating effectively, and delivering on their promises. They’re a trustworthy partner that requires minimal supervision.

Janosch Greber

QA Manager, Secure Mobile Solutions Company