You are already paying for quality. Just not deliberately.
It never arrives as an invoice. It arrives as delayed releases, weekend hotfixes, and business users pulled off their day jobs to re-test the same screens every cycle. None of that sits in a QA budget line. All of it is the QA bill.
Measure it on one release →Nobody buys testing. They buy the end of a problem they had stopped noticing.
Manual regression is the largest recurring cost in most testing operations, and the easiest to remove. TECH ECS delivers Quality Engineering and Testing across web, mobile, API, Oracle, Salesforce and SAP applications, for organisations in Banking and BFSI, Airlines, Telecom, Oil and Gas, Real Estate, and Life and Auto Insurance.
Four things you already live with.
None of these gets filed as a testing problem. All four are.
Releases slip
Every release waits on a manual regression pass that takes days or weeks. The date moves, and it gets recorded as a delay rather than a testing problem.
UAT is a tax on the business
Finance, HR and operations staff spend weeks clicking through test scripts, every release, forever, doing work they were not hired to do.
Defects reach production first
Customers or staff find them before you do. Each one costs a hotfix, an apology, and a little of the trust you had built.
Nobody can answer what was tested
No coverage picture, no evidence trail, and no way to know whether this release is safer or riskier than the last one.
The later you find a defect, the more you pay for it.
Shift-Left Quality Engineering moves testing forward into the build cycle instead of leaving it as a gate at the end. The same defect, found earlier, costs a fraction of what it costs in production.
Tested from the start
Testing begins with the requirement rather than after the code, so gaps surface while they are still cheap to close.
Automated on every build
Regression runs through CI/CD on each build, not once at the end when the release window is already tight.
Decided on evidence
Coverage data and defect trends replace confidence and judgement as the basis for a go or no-go call.
Testing across the stack, not just the screen.
Functional, non-functional and specialist application testing from one team. Take the part that hurts most and leave the rest.
Functional Testing
Web, mobile, API, Oracle, Salesforce and SAP applications, tested against what the business actually needs them to do.
Automation Testing
Model-based automation with Tricentis Tosca and Vision AI, API automation, and integration into your CI/CD pipeline.
Performance Engineering
Load, stress, endurance and scalability testing with JMeter, run before your next peak rather than during it.
Security Testing
OWASP coverage, authentication and authorisation testing, and vulnerability validation across your applications.
Salesforce Testing
Sales Cloud, Service Cloud and Marketing Cloud, along with CRM and CMS platforms in the wider estate.
Oracle Application Testing
Webforms and Winforms, legal entity creation, accounting setup and distribution flows.
Mobile Testing
Native and hybrid applications across Android and iOS, on real device coverage rather than emulators alone.
Database & Integration
Data integrity, interfaces and end-to-end flows across the systems your applications depend on.
UAT & Production Validation
Support through the UAT cycles your business team runs, plus validation and release support after go-live.
Five stages. Measured at both ends.
The point of the first engagement is not to sell you a QA function. It is to put a number on what a release currently costs.
Assess
One application, one release cycle. What is tested, what is not, and how much of it is manual.
Baseline
Current regression duration, coverage and defect leakage, recorded before anything changes.
Automate
The regression suite built in Tosca, with reusable components that keep maintenance effort down.
Integrate
Wired into your CI/CD and defect tooling so it runs on every build rather than on request.
Measure
The same numbers again. Cycle time, coverage and defects, compared against the baseline.
We work inside the toolchain you already run.
Nothing here asks you to adopt a new stack in order to get started.
API testing
Postman, SOAP UI and Swagger for service and contract level testing.
Device coverage
BrowserStack across browsers and real Android and iOS devices.
Load testing
JMeter for load, stress, endurance and scalability scenarios.
CI/CD and defects
Jenkins builds, with Jira, Azure DevOps or HP ALM for defect and test management.
Three ways to engage, and you can change your mind later.
Agile Scrum, Waterfall or a hybrid that matches how your delivery actually runs, rather than how a methodology says it should.
Managed QA
We own the testing function and deliver against agreed outcomes, with dashboards and metrics you can act on.
Dedicated Teams
A named QA team working inside your delivery structure and your release calendar.
Staff Augmentation
Specific skills added to your existing team for a defined period and a defined scope.
You do not need a QA strategy to begin.
One honest look at what a single release costs you is enough to decide whether any of this is worth doing.
QA health check
One application, one release cycle. What is covered, what is manual, and where the time actually goes.
Regression automation pilot
Automate a single regression suite and measure the cycle time before and after. No commitment beyond the pilot.
Performance baseline
Load and stress test one critical application ahead of your next peak, while there is still time to act on it.
The details, up front.
Our developers test their own work. Is that not enough?
It covers what they changed. It rarely covers what their change affected elsewhere, which is where regression defects come from. That gap widens with every release and every integration.
We already have an internal QA team. What would you add?
Usually capacity and automation rather than replacement. If a large part of your team's week goes to running the same manual regression, automating that layer frees them for exploratory and higher-value testing.
We have never had a serious production issue. Why change anything?
You may be well covered, and if so we will tell you that. The question worth answering is what a serious issue would cost, and whether anyone has checked how the system behaves at peak volume rather than average volume.
Do we have to change our tools?
No. We work inside Jira, Azure DevOps, HP ALM and Jenkins as we find them. Tricentis Tosca is used for automation where it fits, and that is a conversation rather than a condition.
How do you prove it worked?
We record the baseline before we start. Regression cycle time, coverage and defect leakage are measured again afterwards and compared. Reported improvements run between 30 and 70 percent on regression cycles, depending on the application and the starting point.
Do you only test Oracle applications?
No. Oracle is one part of it. We test web, mobile, API, Salesforce, SAP, CRM and CMS platforms, along with the databases and integrations underneath them.
How small can the first engagement be?
One application and one release cycle. That is enough to produce a baseline and a recommendation, and small enough that it does not need a programme approval to happen.
Tell us what you are releasing today.
Share a few details and our Quality Engineering team will reach out to talk through your applications, your release cycle, and how much of your testing is still done by hand.