From 50,000 Tests to Millions of Validations

Traditional tests break when UI elements change (IDs, classes, positions). Self-healing tests use AI to automatically detect and adapt to these changes using visual recognition, semantic understanding, and context clues—eliminating the need for manual test maintenance. When a button ID changes, our AI identifies the element by its visual appearance, surrounding text, and function, updating the test automatically.

Yes, our platform converts plain English test descriptions into executable tests. For example, 'Login as admin, navigate to reports, and verify revenue chart displays last 30 days' becomes a fully functional automated test with proper assertions, error handling, and screenshots. This enables product managers, business analysts, and QA without coding skills to create comprehensive test coverage.

Our continuous learning algorithms analyze every test run to identify failure patterns, discover edge cases, and prioritize high-risk code areas. The AI learns which code changes historically cause bugs, which user flows have the most defects, and which test scenarios provide the best coverage—automatically generating new tests for under-covered areas and evolving existing tests to catch more issues.

We support functional testing, regression testing, visual regression testing, performance/load testing, security testing (AI fuzzing), API testing, cross-browser testing, mobile testing, and accessibility testing. All test types benefit from self-healing capabilities, natural language authoring, and continuous learning algorithms.

Most teams are running their first AI-powered tests within 1-2 weeks. Our platform integrates with existing CI/CD pipelines (Jenkins, GitLab, GitHub Actions), requires no infrastructure changes, and can import tests from legacy tools. The self-healing framework learns your application in the first few runs, becoming more accurate with each deployment.

Yes, our multi-tenant architecture is purpose-built for MSPs managing 50+ client accounts simultaneously. Each client workspace is isolated with dedicated resources, role-based access control, and encrypted data separation. We've tested at 100+ concurrent client environments with zero performance degradation. Our largest MSP customer manages 2,100 projects across 50+ clients on shared infrastructure with consistent sub-second response times.

CogniX.AI integrates seamlessly with legacy frameworks through our universal adapter layer. You can import existing Selenium/UFT/Cypress tests, and our AI automatically refactors them into self-healing equivalents—no manual rewriting required. We support parallel execution across frameworks, allowing gradual migration while maintaining existing test investments. Most MSPs have both legacy and CogniX.AI tests running side-by-side during transition periods of 3-6 months.

Enterprise-grade data isolation with encryption at rest (AES-256) and in transit (TLS 1.3). Each client workspace has separate encryption keys, dedicated storage partitions, and network-level isolation. We're SOC 2 Type II, ISO 27001, and GDPR compliant. Client A cannot see Client B's test data, results, or application details. Independent security audits validate zero cross-client data leakage.

Most MSPs achieve 5-10x capacity increase within 90 days. Our fastest deployment: Asia-Pacific MSP went from 1,200 to 2,100 managed projects in 4 months without adding headcount. The workforce multiplication model means 1 QA engineer + CogniX.AI can manage 15-20 concurrent projects (vs. 4-6 traditionally). Client onboarding accelerates from 16 weeks to 4 weeks, allowing rapid service expansion.

Traditional tests break when UI elements change (IDs, classes, positions). Self-healing tests use AI to automatically detect and adapt to these changes using visual recognition, semantic understanding, and context clues—eliminating the need for manual test maintenance. When a button ID changes, our AI identifies the element by its visual appearance, surrounding text, and function, updating the test automatically. Result: 88% maintenance reduction and zero broken tests after UI updates.

Yes, our platform converts plain English test descriptions into executable tests. For example, 'Login as admin, navigate to reports, and verify revenue chart displays last 30 days' becomes a fully functional automated test with proper assertions, error handling, and screenshots. This enables product managers, business analysts, compliance officers, and QA without coding skills to create comprehensive test coverage. Real impact: Healthcare SaaS achieved 90% test coverage (up from 20%) with zero specialized automation hires, saving $900K annually.

Our AI analyzes code changes and predicts which tests are likely to fail based on change impact analysis, historical failure patterns, and risk weighting. Instead of running all 50,000 tests (48 hours), we intelligently select 7,500 high-risk tests (6.5 hours) with zero quality degradation. Continuous learning means the model gets smarter with each run, improving accuracy over time. E-commerce enterprise achieved 26x faster deployments using intelligent selection.

Audit-ready compliance with SOX, HIPAA, GDPR, PCI-DSS, and ISO 27001 templates. Automated audit trails capture who ran which tests, when, and what results were produced. Immutable test result storage for regulatory inspections. Role-based access control with separation of duties (test creator ≠ test executor). Automated compliance reporting with evidence packages for auditors. Financial services customer achieved 80% faster SOX compliance testing with built-in audit trails.

Specialized AI testing capabilities including ML model validation (accuracy, precision, recall), bias detection across protected classes, data drift monitoring, LLM hallucination detection, prompt injection testing, and model regression testing. We validate fairness metrics (demographic parity, equalized odds) for Fair Lending, EEO, and GDPR compliance. Automated retraining triggers when model performance degrades. Explainability testing ensures AI decisions are interpretable for compliance and trust.

Most organizations achieve positive ROI within 90 days. Cost per test case drops from $500-1,500 (manual) or $150-400 (legacy automation) to $50-150 (CogniX.AI)—a 70-90% reduction. Service margin improvement from 12% to 22-35% for MSPs. Workforce multiplication (5-10x capacity without proportional headcount) delivers immediate cost savings. Typical payback period: 3-6 months for mid-size deployments, 6-12 months for enterprise-wide implementations.

Most teams are running their first AI-powered tests within 1-2 weeks. Enterprise-wide rollout (50,000+ tests) typically takes 3-6 months with gradual migration from legacy frameworks. Our platform integrates with existing CI/CD pipelines (Jenkins, GitLab, GitHub Actions), requires no infrastructure changes, and can import tests from Selenium, UFT, Cypress. The self-healing framework learns your application in the first few runs, becoming more accurate with each deployment. MSPs typically onboard new clients in 4 weeks (vs. 16 weeks traditionally).

Agentic AI testing represents autonomous testing agents that continuously adapt, execute, and escalate without human intervention. These agents analyze code commits in real-time, generate tests dynamically, execute validations across environments, and escalate failures intelligently based on severity and business impact. Early adopters have achieved 30x faster deployment (commit → production in 45 minutes vs. 24+ hours). Current beta program available for select enterprise customers. General availability planned for Q3 2025.