Enterprise Quality Engineering
Quality at the speed of enterprise change. Engineer confidence into every release.
Quality Engineering built for modern applications, data platforms, enterprise systems, and AI. Prolifics embeds intelligent automation, continuous validation, and risk-based assurance across the software lifecycle — so you release faster, with less production risk.
The enterprise quality challenge
Software is moving faster. Quality must move earlier.
Cloud modernization, API ecosystems, mobile experiences, data migrations, SAP transformations, and AI-generated software are increasing both delivery speed and operational complexity.
When quality remains a final checkpoint, defects surface late — where they are more expensive, more disruptive, and more visible to customers.
Enterprises need a QE model that can
Prevent, not just detect
Stop defects being created instead of finding them after the fact.
Target real business risk
Connect testing priorities to critical customer journeys, not test volume.
Scale without brittleness
Grow automation without creating a high-maintenance test estate.
Validate as one system
Applications, integrations, data, infrastructure, and AI behavior together.
Produce auditable evidence
Continuous release evidence across DevOps and CI/CD pipelines.
Protect compliance
Performance, security, accessibility, privacy, and regulatory obligations.
Our quality engineering approach
Build quality in. Prove it continuously.
Prolifics combines consulting, domain expertise, automation, governance, AI, and proprietary accelerators across the full delivery lifecycle. We work with your teams and technology landscape, not around them.
Baseline the risk
Evaluate QE maturity, application risk, business-critical journeys, automation health, tools, skills, data, and environments. Define an outcome-led roadmap.
Build the model
Create the target operating model, automation architecture, quality gates, reusable frameworks, metrics, and governance needed to scale.
Execute at breadth
Execute functional, API, integration, data, mobile, performance, security, accessibility, AI, and enterprise-platform testing.
Embed the feedback
Embed tests and evidence into CI/CD, release workflows, service management, and production monitoring for continuous feedback.
Get ahead of defects
Apply analytics and AI to optimize coverage, prioritize risk, detect patterns, forecast quality issues, and continually improve outcomes.
By design, not by accident
Use AI to expand speed and coverage while people retain accountability for context, judgment, governance, and release decisions.
Comprehensive enterprise QE services
One quality partner across your digital estate.
Sixteen service areas spanning strategy, engineering, automation, and managed delivery — applied to the systems that carry your business.
Quality strategy & maturity assessment
Business-aligned QE strategy, target operating model, roadmap, toolchain, metrics, and investment priorities.
Functional & business process testing
Validate requirements, end-to-end workflows, rules, calculations, user journeys, and business outcomes.
Test automation & continuous testing
Reusable automation for UI, web, desktop, mobile, API, regression, and CI/CD — low-code and AI-assisted.
Integration, API & microservices testing
Contracts, payloads, orchestration, error handling, service virtualization, middleware, and third-party links.
Performance & resilience engineering
Response time, throughput, scalability, endurance, recovery, reliability, and SLA readiness under real demand.
Security, privacy & compliance testing
Vulnerabilities, security controls, privacy requirements, regulated workflows, and auditable pre-release evidence.
Accessibility & inclusive experience
Automated checks plus expert-led validation against applicable accessibility expectations.
Mobile & omnichannel testing
Functionality, compatibility, usability, performance, and consistency across devices, OSs, browsers, channels.
Data, ETL & migration validation
Source-to-target reconciliation, schema and transformation validation, cross-database and high-volume checks.
Test data management
Discovery, PII identification, masking, subsetting, synthetic data, and automated compliant delivery.
AI test automation
Intelligent generation, impact analysis, risk-based prioritization, predictive insight, and self-healing.
Testing for AI, GenAI, RAG & agents
Output quality, grounding, hallucination risk, bias, safety, robustness, tool use, memory, and outcomes.
Enterprise application testing
SAP, Salesforce, Microsoft Dynamics, cloud platforms, and connected enterprise processes.
Managed testing services & TaaS
Outcome-aligned capacity, governance, automation, reporting, and continuous improvement, delivered globally.
Testing Center of Excellence
Standard methods, architecture, assets, tooling, metrics, knowledge, and governance for federated teams.
Release assurance & quality intelligence
Quality signals in dashboards and gates that support traceable, risk-informed release decisions.
AI-powered quality engineering
Who tests the software AI builds, and the AI itself?
AI changes both sides of the quality equation. Teams increasingly use AI to generate code, tests, interfaces, and workflows. At the same time, enterprises are releasing probabilistic systems that retrieve information, generate answers, call tools, maintain state, and act.
Human + AI quality engineering
AI accelerates analysis, test design, scripting, execution, and triage. Quality professionals supply business context, challenge assumptions, review evidence, and retain accountability.
Testing AI-generated software
Validate correctness, maintainability, security, dependency choices, compliance, and business alignment — not simply whether generated code runs.
Testing AI systems
Assess models, prompts, RAG pipelines, agents, and AI-enabled workflows for relevance, grounding, accuracy, bias, toxicity, robustness, privacy, explainability, and safe failure.
Agentic QE & predictive quality
Coordinate specialized agents across requirements, test generation, data, execution, analysis, and reporting while using quality signals to focus effort before defects become incidents.
Governance is part of testing
Testing produces the evidence that AI governance needs. Governance defines the policies, thresholds, ownership, human oversight, and auditability that AI testing must verify.
Prolifics quality accelerators
Accelerators selected for the quality problem, not forced onto the landscape.
Each one reduces reinvention, shortens time to value, and integrates with existing tools. The amber chip names the constraint it removes.
Quality Fusion™
Fragmented TestOpsAn integrated Test Automation and TestOps accelerator that unifies lifecycle visibility, automation, metrics, analytics, and release workflows. Code-free automation for web, desktop, mobile, and APIs; integrates with CI/CD and DevOps; runs in cloud, hybrid, or on-premises.
AI TestForge
Inconsistent AI evaluationA structured evaluation capability for LLM, RAG, and agentic applications. Define repeatable test suites, quality criteria, datasets, scoring, evidence, and regression practices for systems whose outputs are probabilistic rather than fixed.
Agentic QE
Manual lifecycle coordinationA governed Human + AI model in which specialized capabilities interpret requirements, propose tests, prepare data, orchestrate execution, analyze results, and assemble evidence — while human experts approve critical decisions and exceptions.
TiDium
Slow, risky test dataAI-powered end-to-end test data management that identifies data types, detects and masks PII, creates context-preserving subsets, and provisions production-like data for faster, safer testing. Deploys on-premises, cloud, and hybrid.
Effecta™
SAP data validation bottlenecksA Prolifics-built validation engine for automated data comparison and impact analysis across SAP and connected non-SAP ecosystems. Transactional validation, document and table comparison, IDoc and integration validation, targeted impact analysis.
IBM-powered testing solutions
Complexity across IBM estatesQE expertise and reusable accelerators combined with IBM technologies to support intelligent automation, predictive insights, continuous testing, data validation, AI assurance, analytics, and lifecycle visibility.
NUVK
Brittle automation maintenanceAn enterprise automation accelerator for intelligent test creation, reduced script maintenance, and self-healing automation.
Reusable frameworks & design assets
Reinvention and slow scalePre-built patterns, test-design assets, automation frameworks, dashboards, integrations, and governance templates that accelerate adoption while remaining adaptable to the client toolchain.
Platforms and toolchain integration
Platform-agnostic engineering. Enterprise-ready integration.
We select, implement, integrate, modernize, and operate testing platforms across the lifecycle — protecting existing investments and choosing technology on application type, risk, architecture, team capability, and target outcomes.
Automation
API & integration
Performance
Security & code quality
DevOps & TestOps
Enterprise platforms
SAP quality assurance & testing excellence
Protect every stage of SAP transformation.
SAP programs combine business-process redesign, custom code, integrations, data migration, performance, security, and user adoption.
Prolifics embeds quality gates across SAP Activate and supports Brownfield, Greenfield, and selective-data-transition programs with domain-led assurance.
- Readiness, fit-to-standard, custom code, and remediation validation.
- End-to-end process testing across order-to-cash, procure-to-pay, record-to-report, supply chain, and industry workflows.
- SAP GUI and Fiori functional and regression automation.
- API, OData, IDoc, middleware, BTP, and SAP-to-non-SAP integration testing.
- Data migration reconciliation, transformation validation, and financial balance checks.
- Performance, volume, stress, batch, cutover, and resilience testing.
- Quarterly-update regression and continuous testing integrated with landscape promotion.
- Effecta-powered document, table, IDoc, comparison, and impact validation.
Industry-aligned quality engineering
Quality priorities change by industry. Our engineering model adapts.
Seven sectors where domain context changes what good quality actually means.
Banking, financial services & insurance
Payments, pricing, transaction integrity, regulatory workflows, APIs, resilience, security, and release evidence across high-volume, always-on systems.
Healthcare & life sciences
Patient, member, provider, and supply-chain experiences with privacy-aware data, workflow assurance, interoperability, performance, and compliance.
Retail, CPG & logistics
Omnichannel journeys, inventory, fulfillment, payments, promotions, mobile experiences, integrations, and peak-event performance.
Energy & utilities
Customer and field-service journeys, asset and grid platforms, integrations, regulatory obligations, reliability, and operational resilience.
Legal
Document-intensive, security-sensitive environments with enterprise automation, integration testing, accessibility, and performance engineering.
Manufacturing
SAP, plant and supply-chain processes, data migrations, integrations, batch workloads, traceability, and business continuity.
Higher education & public sector
Accessibility, security, citizen and student experience, interoperability, legacy modernization, and compliance across diverse populations.
Your sector not listed?
Our engineering model adapts to the risk profile of any regulated, high-volume, or transformation-heavy environment.
Testing Center of Excellence & managed services
Turn testing into a scalable business capability.
A Prolifics Testing Center of Excellence provides shared architecture, governance, assets, skills, tooling, and quality intelligence while enabling product teams to deliver at speed.
Managed Testing Services extend that model with flexible capacity and outcome-aligned operations.
- Federated governance with clear ownership and decision rights.
- Standard methods, quality gates, templates, and reusable automation.
- Tool rationalization, platform enablement, and automation health management.
- Central test data, environment, service virtualization, and knowledge services.
- KPI dashboards for coverage, defect leakage, cycle time, automation stability, risk, and release readiness.
- Onshore leadership with nearshore and offshore execution that scales with demand.
- Service-level and outcome measures tied to business performance — not only test volume.
- Continuous improvement, innovation, and skills enablement to reduce long-term dependency.
Business outcomes
Make quality a measurable advantage.
Eight outcomes that turn quality engineering from a cost centre into a lever on speed, risk, and cost.
Release faster
Shorten feedback, regression, and release cycles through automation and continuous testing.
Reduce production risk
Detect issues earlier and focus effort on the journeys, integrations, data, and systems that matter most.
Increase coverage
Expand validation across UI, API, mobile, data, performance, security, accessibility, and AI.
Lower maintenance
Reusable, low-code, self-healing, and AI-assisted approaches improve automation sustainability.
Strengthen compliance
Traceable evidence across security, privacy, accessibility, regulated workflows, and AI governance.
Improve experience
Protect reliability, performance, accessibility, and end-to-end customer and employee journeys.
Optimize cost
Reduce rework, environment prep, manual execution, production incidents, and tool overhead.
Build release confidence
Give business and technology leaders a transparent, risk-informed view of readiness.
Proof in practice
Representative outcomes from enterprise engagements.
Results delivered across payments, healthcare, retail, legal, and SAP transformation programs.
Quality Fusion increased test velocity from every two days to twice daily, reduced test-cycle time by more than 50%, and increased user-story delivery by 45%.
A Testing Center of Excellence saving more than $1 million annually.
Higher functional coverage, alongside 50% lower test time per cycle, fewer customer escalations, and improved end-user satisfaction.
A program achieving a 70% reduction in test execution time using Tosca automation and Prolifics accelerators.
Enterprise automation using Tricentis Tosca, Vision AI, and NeoLoad to improve automation and establish repeatable performance testing.
A Human + AI approach with governed test design and a roadmap toward agentic quality engineering.
Why Prolifics
Enterprise depth. AI innovation. Quality accountability.
Six reasons enterprises trust us with the quality of the systems they cannot afford to get wrong.
Consulting-led and outcome-driven
We connect QE investment to business risk, customer journeys, operational resilience, and transformation goals.
End-to-end quality coverage
One partner across applications, APIs, data, mobile, performance, security, accessibility, SAP, cloud, AI, and managed delivery.
Automation-first, tool-flexible
Leading commercial and open-source platforms combined with proprietary accelerators — without forcing one tool on every workload.
Human + AI delivery model
AI extends speed, insight, and coverage while people keep accountability, transparent evidence, and governance.
Enterprise-scale experience
30+ years of QE experience, 700+ testing professionals, and more than 20 million testing-service hours.
Global, scalable execution
Flexible onshore, nearshore, and offshore delivery supports transformation programs, products, and ongoing operations.
Engagement models
Start where the risk is highest.
Six ways to engage, from a focused assessment to fully managed quality operations.
QE maturity assessment
Establish the current-state baseline, priority risks, target capabilities, and transformation roadmap.
Automation health check
Evaluate coverage, stability, maintenance, frameworks, tools, pipelines, and AI-assisted modernization opportunities.
Focused proof of value
Validate a high-value use case for AI Test Automation, Testing for AI, Agentic QE, test data, SAP assurance, or performance.
QE transformation program
Implement the target operating model, TCoE, platforms, accelerators, automation, governance, and adoption roadmap.
Managed testing services
Run end-to-end quality services with scalable capacity, transparent outcomes, and continuous improvement.
Specialist engineering services
Targeted expertise in performance, security, accessibility, data migration, SAP, AI assurance, or complex integration testing.
Let’s talk
What is slowing your release confidence?
Whether you are modernizing an established testing practice, scaling automation, validating an SAP or data transformation, or preparing AI systems for production, we can help you find the fastest path to measurable quality outcomes.
- Assess your current QE maturity and risk profile.
- Identify high-value automation and AI opportunities.
- Select the right accelerators and platforms for your landscape.
- Build a practical roadmap from reactive testing to predictive quality.