Product Engineering

Mobile App Development

Stop writing tests.
Start governing quality.

ScalexQA deploys production-grade agentic pipelines that reconcile your PRDs, OpenAPI specs, and design references against your running application — generating, executing, and repairing tests with zero manual authoring.

Stop manual QA from throttling your CI/CD pipeline with autonomous agents.

The Challenge

QA isn't a writing problem, it's a pipeline problem

In a world of multiple daily deployments, manual and traditionally automated QA have become bottlenecks rather than feedback loops.

The Solution

The Autonomous Agentic Workforce

ScalexQA utilizes a specialized roster of Mastra AI agents to manage the entire testing lifecycle, keeping humans in the loop only for high-stakes, ambiguous calls.

Requirements Ingestion Agent

Intent Mapping
Automatically pulls Jira tickets, OpenAPI specs, and Figma designs, normalizing them into structured testing "intent" blocks.

Discovery Agent

Automated Code Synthesis
Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Test Authoring Agent

Automated Code Synthesis
Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Independent Judge Agent

Supervisory Model Cross-Check
A supervisory agent running on an isolated model architecture that scores newly authored tests for relevance and design conformance. If confidence drops below your project's threshold, it triggers a mandatory human review.

Diagnostics & Remediation Agents

Self-Healing Pipeline Loops
On failure, these agents inspect stack traces and DOM snapshots to classify root causes. They autonomously patch selector drift or open a PR for human review when a genuine regression surfaces.

Close the testing gap with agents that auto-remediate flaky tests.

The Trust Architecture

Safety by Design

We believe AI in QA is only as good as the guardrails surrounding it. ScalexQA is built on a strict Supervisory Model.

Progressive Web Apps

We offer Progressive Web Apps (PWAs) that provide fast loading times and high reliability without needing installation. Our PWAs deliver a native-like user interface and experience, complete with features like notifications.

Mobile App Testing and QA

Ensuring the quality, performance, security, and usability of mobile applications through various testing methods, including functional testing, performance testing, usability testing, security testing, and compatibility testing across different devices and OS versions.

MobilityOps

We use agile methods to quickly develop and deploy apps. Automation helps us make the process easy, so you can reach your audience fast. Our team handles app deployments on Google Play and the Apple App Store and provides automated testing with CI/CD for smooth performance.

Shadow vs. Gating Modes

All new suites run in SHADOW mode — recording evidence and visibility without ever failing a build — until a human explicitly promotes them to GATING.

Zero Correlated Blind Spots

To ensure the AI isn’t "grading its own homework," the Judge Agent runs on a completely different model family (e.g. Anthropic) than the Authoring Agent (e.g. a local Ollama instance).

Configurable Confidence

You define the thresholds. Auto-remediation only applies to low-risk issues like selector drift when the agent’s confidence exceeds your preset limit (e.g. 80%).

Industries & Domains

Built for High-Stakes Domains

Our framework is purpose-built for engineering teams where quality is non-negotiable and delivery speed is a competitive advantage.

Logistics & InsurTech

Cover complex rules engines and sprawling integrations that single-source specifications often miss.

FinTech

Ensure high-stakes correctness with 100% traceability from regulated flows to test evidence.

Healthcare Technology

Support evidence-backed, zero-downtime releases where reliability and compliance are paramount.

Bring agentic testing to your high-velocity team without risking broken builds.

The Scalex Engagement Model

From First Crawl to Gating Suites in Weeks

We stand ScalexQA up on one service, prove it in shadow mode, then expand — you see working evidence before anything gates your pipeline.

Weeks 1

Discovery & Scoping

We map your requirement sources, crawl a target service to expose coverage gaps, and stand up the agent pipeline.

Weeks 2

Authoring & Shadow Runs

We generate the first test suite, run it through independent Judge review, and shadow-run it against your app so it blocks nothing.

Weeks 3 - 4

Go-Live & Pipeline Integration

We enable automated triage and confidence-gated self-healing, tune the human-in-the-loop thresholds, and promote trusted suites to gating in your CI loop.

Frequently Asked Questions

If you can't find what you're looking for, please reach out to our team for further assistance.

How do you prevent the AI from approving its own flawed tests?

We utilize an independent Judge Agent. By configuring the Judge to run on a completely different AI model family than the Authoring Agent (e.g., pointing one at a hosted cloud model and another at an internal local model), we ensure a genuinely independent review that eliminates correlated blind spots.

Will unproven AI tests break our CI pipeline?

No. All newly generated test suites strictly run in "SHADOW" mode. They provide visibility and record evidence of behavior, but they will never fail a build until a human explicitly approves the suite for "GATING" mode.

What happens when our UI changes and breaks tests?

The Diagnostics Agent immediately inspects the failure. If it classifies the failure as "Selector Drift" and its confidence clears your project's threshold, the Remediation Agent will automatically patch the test code and re-run it to confirm the fix—no human intervention required.

Are we locked into a specific AI provider for this to work?

Not at all. Our framework is built on a model-agnostic interface via Mastra AI. You can configure agents to use hosted APIs (like Anthropic, OpenAI, or Google) or rely on fully self-hosted, credential-free local instances (like Ollama running Gemma).

Generative AI

Data & AI

Product Engineering

Cloud & DevOps

Product Innovation Lab

Product Engineering

ScalexOps AI

ScalexQA Engine

FinTech

InsurTech

Healthcare

Logistics

Stop writing tests. Start governing quality.

ScalexQA deploys production-grade agentic pipelines that reconcile your PRDs, OpenAPI specs, and design references against your running application — generating, executing, and repairing tests with zero manual authoring.

Stop manual QA from throttling your CI/CD pipeline with autonomous agents.

The Challenge

QA isn't a writing problem, it's a pipeline problem

In a world of multiple daily deployments, manual and traditionally automated QA have become bottlenecks rather than feedback loops.

The Velocity Gap: Manual test authoring cannot keep pace with CI/CD; coverage chronically lags behind features.

The Maintenance Tax: Brittle UI tests break on minor markup changes, leading to "flaky" suites that teams eventually ignore.

Triage Fatigue: Engineers spend hours distinguishing real regressions from environment flakes before they can even begin a fix.

Requirements Drift: As requirements evolve, executable tests quickly begin validating stale, outdated behaviors.

The Solution

The Autonomous Agentic Workforce

ScalexQA utilizes a specialized roster of Mastra AI agents to manage the entire testing lifecycle, keeping humans in the loop only for high-stakes, ambiguous calls.

Requirements Ingestion Agent

Intent Mapping Automatically pulls Jira tickets, OpenAPI specs, and Figma designs, normalizing them into structured testing "intent" blocks.

Discovery Agent

Automated Code Synthesis Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Test Authoring Agent

Automated Code Synthesis Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Independent Judge Agent

Supervisory Model Cross-Check A supervisory agent running on an isolated model architecture that scores newly authored tests for relevance and design conformance. If confidence drops below your project's threshold, it triggers a mandatory human review.

Diagnostics & Remediation Agents

Self-Healing Pipeline Loops On failure, these agents inspect stack traces and DOM snapshots to classify root causes. They autonomously patch selector drift or open a PR for human review when a genuine regression surfaces.

Close the testing gap with agents that auto-remediate flaky tests.

The Trust Architecture

Safety by Design

We believe AI in QA is only as good as the guardrails surrounding it. ScalexQA is built on a strict Supervisory Model.

Progressive Web Apps

Mobile App Testing and QA

MobilityOps

Shadow vs. Gating Modes

Zero Correlated Blind Spots

Configurable Confidence

Industries & Domains

Built for High-Stakes Domains

Our framework is purpose-built for engineering teams where quality is non-negotiable and delivery speed is a competitive advantage.

Logistics & InsurTech

Cover complex rules engines and sprawling integrations that single-source specifications often miss.

FinTech

Ensure high-stakes correctness with 100% traceability from regulated flows to test evidence.

Healthcare Technology

Support evidence-backed, zero-downtime releases where reliability and compliance are paramount.

Bring agentic testing to your high-velocity team without risking broken builds.

The Scalex Engagement Model

From First Crawl to Gating Suites in Weeks

We stand ScalexQA up on one service, prove it in shadow mode, then expand — you see working evidence before anything gates your pipeline.

Discovery & Scoping

Authoring & Shadow Runs

Go-Live & Pipeline Integration

Frequently Asked Questions

If you can't find what you're looking for, please reach out to our team for further assistance.

Get in Touch!

Proud partner of:

Media accolades:

Company

Services

Subscribe to Our Newsletter!

Stop writing tests.
Start governing quality.

Intent Mapping
Automatically pulls Jira tickets, OpenAPI specs, and Figma designs, normalizing them into structured testing "intent" blocks.

Automated Code Synthesis
Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Automated Code Synthesis
Synthesizes intent and discovered flows to write production-grade code (Gherkin to Playwright/Supertest), filling gaps without duplicating existing suites.

Supervisory Model Cross-Check
A supervisory agent running on an isolated model architecture that scores newly authored tests for relevance and design conformance. If confidence drops below your project's threshold, it triggers a mandatory human review.

Self-Healing Pipeline Loops
On failure, these agents inspect stack traces and DOM snapshots to classify root causes. They autonomously patch selector drift or open a PR for human review when a genuine regression surfaces.