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Analytics & Testing
Analytics, QA & Testing
Comprehensive quality assurance and data-driven insights — so every release ships fast, stable and measurable.
Speed without quality is just faster failure. We build automated test suites and QA processes that catch regressions before users do — and analytics that tell you what actually happened after you shipped.
From unit and end-to-end automation to load testing and release gates, quality becomes a property of your pipeline instead of a manual chore at the end.
We aim test effort where failure is expensive rather than where coverage is easy: the checkout, the login, the billing job, the data import. A suite built that way stays fast enough to run on every commit and trusted enough that a red build actually stops a release — which is the entire point of having one.
The analytics half of the practice closes the loop after release: event tracking with a schema someone actually designed, funnels around the actions that earn revenue, and dashboards that answer questions rather than decorate meetings. Shipping safely and knowing what shipping achieved are two halves of the same discipline.
What's included
Test Automation
Unit, integration and E2E suites with Jest, Cypress, Selenium and Playwright.
Manual & Exploratory QA
Structured test plans and exploratory passes that scripts alone miss.
Performance & Load Testing
Know your breaking point before your users find it.
Product Analytics
Event tracking, funnels and dashboards that turn behavior into decisions.
Release Engineering
Quality gates, canary releases and rollback strategies in CI/CD.
Technologies we reach for
- Jest
- Cypress
- Selenium
- Playwright
- GA4
Why teams choose us
Regressions Caught Early
Automated suites run on every commit — bugs die in CI, not in production.
Release With Confidence
Quality gates and canary rollouts make Friday deploys a non-event.
Decisions From Data
Product analytics show what users do, not what everyone assumes they do.
Faster Over Time
Test automation compounds — every release gets safer while shipping speed goes up.
Industries we serve
- SaaS
- Fintech
- Healthcare
- Retail & E-commerce
- Enterprise IT
Case study · Health tech
Adding senior capacity to a stalled roadmap
Weekly Release cadence · 2 wks To first commit · Flexible Team size
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How we work
From concept to launch
01
Discovery & Strategy
Requirements gathering, technical feasibility and architecture planning — we define the fastest path to measurable outcomes.
02
Agile Development
Sprint-based design and engineering with continuous integration and daily communication. No bloat — rapid, transparent, iterative delivery.
03
Delivery & Support
Rigorous QA, smooth deployment, performance monitoring and ongoing maintenance — a product engineered to grow.
Frequently asked questions
How much test coverage do we actually need?
Enough to deploy without fear — usually critical-path E2E tests plus solid unit coverage on business logic. We target risk, not a vanity percentage.
Can you add tests to an existing untested codebase?
Yes — that is a common engagement. We start with E2E tests over your critical user journeys for immediate safety, then grow coverage inward as code gets touched.
Which testing tools do you use?
Playwright or Cypress for E2E, Jest for unit/integration, Selenium where legacy grids demand it, k6 or Locust for load. The stack adapts to yours, not vice versa.
What analytics setup do you recommend?
GA4 plus a product analytics layer (event tracking with a clean schema) sized to your questions. We implement tracking plans, dashboards and alerting — data you will actually use.
What does a QA engagement cost?
A test-automation foundation over your critical paths typically runs $4k–$11k; ongoing QA embedded in your team is priced monthly like our dedicated-team work. Load testing and analytics implementations are usually scoped as fixed add-ons once we see the system.
Our developers already test — why a dedicated QA effort?
Developers test what they built the way they meant it to work; QA tests the way users actually behave — wrong order, double clicks, bad data, slow networks. Both matter. We also bring the release-engineering piece: gates, canaries and rollback plans that individual feature testing never covers.
When should we load test?
Before the event you are worried about, not after it: a launch, a marketing push, a seasonal peak, a contract with an SLA. One structured load test tells you your real breaking point and what fails first — which turns capacity planning from guesswork into a to-do list.
Ready to talk qa & testing?
Tell us what you're building. If it ships software, we can help.