When defects escape to production, when releases slip, when automation budgets disappear into frameworks that never scale. The root cause is almost always a QA function that was not built to match the pace of the business. Prudentis builds it right.
Whether you need to fill a single specialist seat or hand off your entire testing function, we match the engagement model to your actual situation, not to what is easiest for us to staff.
Place senior QA engineers (manual, automation, performance, or accessibility specialists) directly inside your sprint teams. Our practitioners come with deep domain experience, not just toolchain familiarity. They integrate within days, not weeks.
Transfer full accountability for your testing function to us. We own strategy, execution, defect tracking, reporting cadence, and continuous improvement. You get weekly metrics reviews, monthly quality reports, and a team that escalates issues before they become your problem.
If your QA practice is manual, ad-hoc, or structured around a tool rather than a strategy, we redesign it. We stand up Testing Centres of Excellence, define governance frameworks, implement traceability matrices, and build the measurement culture that makes quality sustainable.
We architect and build GenAI-powered automation frameworks. Our proprietary QABolt platform generates test cases from user stories in minutes, produces realistic test data at scale, and updates your test management tools automatically after every run. No licence lock-in. Built to grow with your product.
Building and maintaining an automation framework typically consumes 2–6 weeks of engineering time before a single test runs. QABolt changes that equation. It converts acceptance criteria into executable test scripts in minutes, generates realistic test data on demand, and keeps your test management tools current without manual intervention.
Converts user story acceptance criteria into complete test cases and automation scripts. What previously took 3–5 story points of manual effort happens in minutes.
Produces realistic, schema-aware test datasets at scale, up to a million records when needed, eliminating one of the most time-consuming bottlenecks in test preparation.
Connects natively with Jira, Zephyr, X-Ray, QTest, TestRails, Jenkins, and CircleCI. Test status updates automatically after every run: 300 to 500 regression cases in seconds, not six hours.
Automated WCAG scanning alongside manual assistive technology testing with JAWS, NVDA, and VoiceOver. ARIA compliance, screen reader compatibility, and colour contrast validation built in.
AI-driven failure cause identification, automated report distribution to Slack or Teams, and customisable dashboards that give leadership a real-time view of product quality without chasing the QA team.
For organisations ready to move beyond point automation, our Agentic QA Lifecycle deploys a coordinated system of AI agents, each responsible for a distinct phase of quality assurance, communicating through event-driven architecture, and operating with minimal human intervention. This is not a roadmap. It is live and deployable today.
Parses natural language requirements using LLMs and RAG-based retrieval against your knowledge base. It extracts functional requirements and acceptance criteria, and flags ambiguities before a single test case is written.
Automatically generates structured test cases and, for UI-heavy workflows, dynamically produces UiPath XAML automation files. Outputs go directly into your test management system with full traceability.
Creates realistic, schema-validated test datasets covering positive, negative, and edge cases. Handles anonymisation for compliance and formats data for immediate consumption by the execution pipeline.
Orchestrates execution across UiPath, Playwright, and custom frameworks. Monitors job status in real time, captures screenshots and logs, and implements configurable retry logic for transient failures.
AI-driven root cause analysis against historical defect patterns, automatic severity and priority assignment, Jira tickets pre-populated with evidence, and Slack alerts within minutes of failure.
Aggregates execution data, generates LLM-written executive summaries, updates test management fields, and pushes KPIs to Tableau dashboards so leadership always has an accurate, current view of quality.
We audit your current QA maturity: toolchain, test coverage, defect escape rates, CI/CD alignment, and team structure. No assumptions. The diagnosis shapes the prescription.
We define the service model, automation framework, reporting cadence, and KPIs that match your release rhythm and business risk profile. We recommend what fits you, not what is convenient for us.
Our practitioners join your delivery teams. Smoke, sanity, regression, and integration suites are built and maintained in parallel with development so defects surface early, not at release.
Weekly quality cadence reviews, defect severity indexing, coverage trending, and Quarterly Business Reviews. Every report answers one question: is quality getting better, and by how much?
A broad capability set means you are never constrained by a single vendor, methodology, or toolchain preference.
Results drawn from active delivery engagements. Every metric is tied to a specific intervention, not to general industry benchmarks.
Achieved through API integration health checks running 24/7, automated regression suites triggered on every build, and a structured defect-tracking process that eliminated escapes to production.
Compressing regression cycles from multi-day manual runs to hours of automated execution. QA engineers get that time back to focus on exploratory and high-judgement testing where human insight matters most.
Achieved by replacing manual smoke testing cycles with automated suites, reducing the team effort needed per release by 40% while simultaneously increasing coverage to end-to-end scenarios.
From zero automation to near-total smoke coverage within a single engagement, including Salesforce integrations, external API health checks, and multi-system regression across parallel release tracks.
Automation frameworks that scale with product growth, with no commercial licence constraints, reduce the marginal cost of every additional test case as the suite expands.
Replacing manual sanity testing before each bi-weekly release with an automated suite covering 100+ test cases. That returns two full days of engineering capacity to every delivery team on every cycle.
A thirty-minute conversation is usually enough to identify where the biggest risk sits and what the right first move is.
Schedule a ConversationPrudentis was built by a QA practitioner with 18 years of hands-on delivery inside some of the world's most demanding engineering organisations. We exist to give technology leaders a smarter alternative to generic staffing and checkbox testing.
The Latin root of prudentis means foresight and sound judgement. It is the right word for what QA actually demands. A defect that escapes to production costs, on average, thirty times more to fix than one caught at the unit testing stage. An automation framework built around the wrong tool locks a team into years of maintenance overhead. A QA practice siloed from the development process produces reports, not quality.
We started Prudentis because most organisations know their QA function is not working as well as it should, yet they are being sold tooling and headcount when what they actually need is a coherent strategy backed by people who have built and run QA programmes at enterprise scale.
Our founder progressed from QA Engineer to Principal Architect across enterprise networking, cloud platforms, media, and financial services. He built the QABolt automation platform, leading 30-person QA teams, and managing programmes across organisations including Cisco Meraki, Yahoo, and ESPN. That operational depth is what every Prudentis engagement draws from.
You will not be handed to a bench-warming account team after the contract is signed. The person who built this business remains accessible and responsible for outcomes throughout.
We assess your situation before recommending anything. The right automation framework for one product is the wrong choice for another. Tool-agnostic thinking is how we protect your investment.
Defect escape rates. Test cycle time. Coverage depth. Cost per test. These are the numbers that matter to a CTO or VP of Engineering. That is what we track and report.
Knowledge transfer is not optional. Every engagement includes structured handover, documentation, and internal capability building. When we are done, your team owns what we built.
QABolt is built on open-source foundations. The frameworks we build are yours. We have no incentive to make you dependent on us beyond the value we actually deliver.
Broad QA knowledge matters. Deep domain experience is what allows us to ask the right questions in the first week and make the right recommendations before the first sprint ends.
Full QA architecture, automation, and managed testing for cloud-managed networking products, including API health check automation running 24/7, regression suite design across multi-system releases, and CI/CD integration across large distributed engineering organisations.
End-to-end Salesforce QA covering SFDC regression automation, no-code and scripted test approaches, requirements traceability via Zephyr, and integration testing across MuleSoft APIs, third-party connectors, and complex multi-org environments.
Data-intensive application testing with up to 100 fields per workflow, WCAG 2.1 accessibility compliance for web and mobile, automated file handling and database transaction validation, and parallel release management without testing bottlenecks.
Functional, accessibility, and performance testing for high-traffic digital products where audience retention depends on sub-second response times and every feature change carries reputational risk at scale.
QA transformation programmes that move organisations from manual, ad-hoc testing to structured, automated practices. This covers Testing Centre of Excellence design, governance model implementation, and KPI frameworks tied to engineering delivery metrics.
Hybrid mobile QA strategy pairing cloud-based real-device testing for hardware-specific scenarios with emulator-based automation at scale, covering iOS and Android simultaneously without the cost and maintenance overhead of a physical device lab.
Familiarity with a tool is not the same as knowing when to use it and when not to. Our practitioners have built production systems with these technologies.
Tell us where your testing stands today and we will give you an honest view of what it should look like and what it would take to get there.
Talk to UsWe respond to every enquiry within one business day with a clear point of view, not a brochure. For urgent staffing needs, we can present shortlisted candidates within 72 hours.
We work best with CTOs, VPs of Engineering, QA Directors, and Product leaders who are ready to make quality a genuine competitive advantage and need a partner who understands what that actually requires.
A member of our team reads every submission personally. We will come back to you within one business day with a direct response, not an automated sequence, and where relevant, a brief perspective on your situation based on what you have shared.
The more context you share, the more useful our first response will be.