Built for AI systems, not adapted to them.
Human review in every workflow.
Checked at each stage, not at the end.
Assurance across the full development lifecycle.
Developers now build features with AI copilots, create autonomous agents and deploy LLM-powered systems. Traditional QE — scripted, reactive, human-bottlenecked — was designed for deterministic code, not for this.
Many QE providers have added AI to a process that was designed years ago. We started from the other end. NexaQ validates AI systems, tests with AI and helps teams adapt, and people and AI work together in every step.
Our Agent Squad is a growing roster of AI agents, each built for a specific quality task, so quality keeps up as your releases speed up.
The NXQ Community brings together quality engineers, AI practitioners and technology leaders who want to get better at testing and validating AI. Members share what they are learning, exchange ideas and stay close to where the field is heading.
Our three service lines cover every layer: AI application assurance, AI-powered digital assurance, and QE advisory for ADLC transformation. Together they deliver continuous assurance across the full software and AI development lifecycle.
Independent validation of LLMs, AI agents, copilots and enterprise AI systems, so they are accurate, reliable, secure and ready for production.
AI-driven test design, generation and orchestration for web, mobile, API and cloud applications, with quality checked continuously across every release.
AI-driven test design, generation and orchestration for web, mobile, API and cloud applications, with quality checked continuously across every release.
Find the right assurance for what you need to validate, automate or transform.
See how quality engineering applies in your sector.
From LLMs and AI agents to web, mobile, API and cloud platforms.
Solutions organized for QA leaders, engineering heads, AI teams and risk owners.
The NexaQ Agent Squad is a growing roster of purpose-built AI agents, each specializing in one critical layer of quality engineering. They work together across the full QE lifecycle, from first requirement to final insight.
Reads feature specs and user stories and produces structured test cases with preconditions, steps, expected outcomes and edge cases. This is where every QE cycle starts.
Turns test cases into executable automation scripts across Cucumber, Playwright and WDIO, and handles locators, page navigation and assertion logic.
Stress-tests applications under load and flags performance bottlenecks before a release goes out.
Runs OWASP Top 10 checks, authentication bypass testing, injection validation and API security audits, with severity ratings and remediation priorities.
Brings together results from the other agents and produces structured reports, risk heat maps, trend analysis and executive summaries. It closes the loop on every test cycle.
Every sector has its own release pressures, compliance needs and pace of AI adoption. Here is how we support some of them.
Validation for AI features, copilots and agent-based products from teams building with AI.
Audit-ready assurance for AI-driven and digital applications where accuracy and compliance matter most.
Reliable, compliant quality engineering for patient-facing and regulated applications.
Quality engineering support for organizations modernizing how they deliver with AI.
Talk to our team about validating your AI applications, modernizing your testing or planning your move to the Agentic Development Lifecycle.
