AI-powered software QA/QE
- We ensure our clients’ software, AI applications, and processes fulfil predefined criteria and standards with the best-in-class AI accelerators and frameworks.
- With over 42 years of experience in software quality, helping our partners with their testing needs, Expleo has been placed in the Leaders Quadrant in the AI space for 2024 by Nelson Hall.
- Globally we have delivered more than 500 live software projects, supported by a network of over 6000 Expleo test consultants.
Custom solutions for your needs
Best-in-class QA and QE resources for Agile teams
- Software QA analysts
- Test automation engineers
- Performance testing engineers
- All equipped with leading edge software testing methodologies and tools.
Test factory for large critical systems
- Function testing
- Predictive and prescriptive quality assurance
- Security testing
- Resilience and failover testing
Software testing assessment, transition and transformation
- Maturity assessment: Methodologies, infrastructure, writing standards, test reports, automation level and output clarity.
- Transformation: Cloud, CI/CD integration, test harnesses, shift-left, coaching of dev, etc.
Trends shaping the industry
Increasing software release rate with the emergence of Agile, DevOps and CI/CD.
The growing complexity of software systems.
Interconnection of systems implies that inadequately tested code could lead to devastating issues.
AI in automation and manual testing with shift left.
These trends highlight the need to release software with the least number of critical bugs while maintaining high development speed and efficient development costs, which requires highly efficient software testing that integrates well within agile teams and that relies on shift-left approach and automation.
Expleo’s approach: to identify quality issues early for more robust software and faster time-to-market.
State of the art Quality Competence Centre
A proven history of pure play in software testing
- Building on 50 years of testing expertise, including SQS’s legacy as Europe’s software testing leader.
- Decades of refining tools and processes keep Expleo at the forefront of software testing innovation.
Nurturing QA and QE know-how
- Unique in-house Software Quality Academy with hands-on training on current and new best-in-class software quality approaches and tools.
Testing platform
- We combine the AI testing toolchain, processes, and people together on Expleo’s X platform, covering functional and non-functional testing.
Hybrid approach onshore/bestshore
Hybrid model for optimal efficiency
- Local teams managing customer relationships and on-site services in Ireland, the UK, France.
- Widespread presence of experts in best-shore countries for optimised costs, including Morocco, Egypt, India, Romania.
10+ years with a leading insurance organisation case study
- 500+ testing professionals responsible for organisation’s most critical systems: core insurance applications, broker applications, and web portals.
- Scalable approach through automation and hybrid onshore/bestshore teams with standardised ramp-up and ramp-down models.
- Test factory services implementation for complete coverage of the SDLC.
Mastering AI/ML
- Selecting the right AI technologies, including Large Language Models (LLMs), to optimise and automate testing workflows.
- 500 team members specialising in data and AI, leveraging LLM to automate software testing.
- End-to-end data life cycle management to ensure quality from training to inference.
Focus on our AI testing tool – ExpleoSophia – its main features are:
- Automated requirements analysis and engineering by providing content in the most common file formats.
- Functional test cases mapped to QA acceptance criteria, system functionality, integration, and user acceptance testing.
- Model agnostic; can be used across any models powered by OpenAI, Meta, Mistral.
Focus on AI-powered automation tool – ExpleoTeresa- its main features include:
- Self-healing capability (recover from test failures)
- Visual UI testing
- Data-driven testing
- Integration with CI/CD and test/defect management
Preferred software quality partner
of a leading insurance company
Winner of the
TestAutothon 2023 STeP-IN Forum Asia Pacific’s largest testing forum
Leaders quadrant in
AI space - Nelson Hall 2024 to market
FAQ
We deliver our solutions to clients in over 30 countries, including France, Germany, the UK, Spain, Italy, Croatia, Romania, Canada, China, Morocco, and India.
AI technologies are revolutionising QA/QE through intelligent test automation, predictive analytics, and enhanced defect detection. Machine learning algorithms now power self-healing test scripts that automatically adapt to UI changes, while AI-based visual testing tools can detect subtle interface issues human testers might miss. Natural language processing enables test generation from requirements documents, and anomaly detection systems identify potential defects before they reach production.
As for testing AI systems themselves, this requires specialised approaches focused on data quality validation, bias detection, model performance evaluation across diverse scenarios, and robust regression testing to ensure algorithmic stability. Organisations are developing specific frameworks to verify AI output consistency, explainability, and ethical compliance.
QA/QE is more crucial than ever. Instead of replacing quality professionals, AI and automation have enhanced their strategic roles. QA engineers now act as quality consultants using AI tools for deeper insights and comprehensive oversight. With faster development, quality ensures speed does not sacrifice reliability. QA/QE focuses on test strategy, risk assessment, and governance, leaving repetitive tasks to automation.
Testing Centres of Excellence can function effectively in Agile environments when adapted appropriately. Contemporary TCoEs serve as enablement hubs, offering standardised testing frameworks, tools, and specialised expertise to distributed teams. They set quality guidelines while allowing individual Agile teams the autonomy required for quick delivery.
Successful TCoEs in agile organisations focus on test infrastructure management, shared automation frameworks, specialized testing services (like performance or security testing), and continuous quality improvement. They serve as innovation centres, continuously evaluating emerging quality technologies and methodologies to enhance the organization’s testing capabilities while maintaining consistent quality standard.