Testing services that solve release problems.

The problem. Features ship because they worked in the developer's browser — then break on other viewports, states, and flows.

What Cypher QA does. Structured functional and UI passes across real user journeys: navigation, forms, authentication, state handling, and edge cases. Every defect is reported with reproduction steps, evidence, and severity.

The problem. You are close to release and need a fast, honest answer to one question: is this ready?

What Cypher QA does. Time-boxed exploratory sessions focused on the highest-risk areas, ending in a clear status summary per area and an explicit release recommendation — hold, fix and retest, or go.

The problem. Every fix risks breaking something else, and untested regressions quietly accumulate until a user finds them first.

What Cypher QA does. Regression coverage built around your critical workflows — executed manually where judgment matters and automated where repetition pays off, so every release starts from a known baseline.

The problem. A layout that works at 1440px can overlap, clip, or hide critical controls on the phones most of your users actually hold.

What Cypher QA does. Systematic checks across the real viewport range — from 320px phones to ultrawide desktops — covering layout integrity, touch targets, content priority, and interaction behavior at every breakpoint.

The problem. Manual regression cycles grow with every release until they consume the team's entire testing capacity.

What Cypher QA does. End-to-end Playwright suites organized with the Page Object Model, covering critical user journeys with screenshots, video, and traces on failure — so failures are diagnosable, not just red.

The problem. Backend regressions often appear only after the frontend fails — late, noisy, and expensive to diagnose.

What Cypher QA does. Direct REST validation with schema-based response checks, authentication flows, and negative-path coverage. API-level tests catch defects earlier, before any UI is involved.

The problem. Tests that only run on someone's laptop protect nobody once the code leaves it.

What Cypher QA does. GitHub Actions pipelines that run smoke suites on every change and full regression on schedule, publish reports and artifacts, and fail fast with complete failure context.

The problem. Loose collections of test scripts become unmaintainable: duplicated logic, brittle selectors, no consistent reporting.

What Cypher QA does. Purpose-built frameworks with clean architecture — configuration layers per environment, shared fixtures, retry handling, typed models, and integrated reporting. Designed so your engineers can extend them without fighting them.

The problem. A passing UI proves nothing about what your application wrote to the database.

What Cypher QA does. Data validated at the source: SQL assertions against PostgreSQL or SQLite through a managed connection layer, verifying that user actions produce correct, persistent state.

The problem. Defect reports that developers cannot reproduce waste everyone's time and erode trust in QA.

What Cypher QA does. Reproducible step-by-step findings with screenshots or recordings, environment details, severity classification, and expected-vs-actual behavior — formatted to move straight into your issue tracker.

The problem. Requirement analysis, API test scaffolding, and CI failure triage are high-effort, repetitive work that slows coverage down.

What Cypher QA does. Practical AI workflows built and validated in-house: requirements analyzed into structured test cases with boundaries and edge cases, OpenAPI specifications turned into pytest suites, and CI failures triaged into root causes with suggested fixes.

The problem. Non-deterministic features break traditional pass/fail assumptions — teams ship them with far less verification than everything else.

What Cypher QA does. Validation strategies for AI-backed functionality: structured output contracts checked against typed schemas, provider fallback and retry behavior, prompt versioning, and regression approaches suited to probabilistic systems.