Why Obvyr?

Prove Your Tests Work. Don't Just Assume.

Most engineering teams rely on assumptions about test quality. They assume tests are reliable because they pass. They assume their test suite protects production because coverage metrics look good. They assume local testing matches CI behaviour because the codebase is the same.

Obvyr replaces assumptions with proof.

The Problem: Testing Theatre vs. Reliable Testing

Modern engineering teams face a critical challenge: How do you know your tests are actually protecting production?

The Four Testing Crises

1. Flaky Tests Destroying Team Confidence

A test passes locally but fails in CI. It fails on retry, then succeeds. The team starts ignoring failures, assuming "it's just flaky." Eventually, teams lose trust in their entire test suite, and real bugs slip through because no one believes the failures anymore.

The Cost:

Developers waste hours debugging false negatives. Teams ship bugs because they've learned to ignore test failures. Deployment confidence evaporates.

2. Environment Divergence Creating Deployment Uncertainty

Tests pass perfectly in local development. CI is green. But production breaks. The difference? Environment configuration, dependency versions, network behaviour, data state. Traditional testing tools only show you the final result—they don't reveal the systematic differences between where you test and where you deploy.

The Cost:

Production incidents from issues that "passed all tests." Emergency rollbacks. Post-mortems that conclude "our tests didn't catch it."

3. Testing Theatre: Can't Distinguish Value from Noise

Your coverage report shows 85%. You have 3,000 tests. But which tests actually matter? Which ones protect critical user journeys? Which ones are just testing framework behaviour or trivial getters? Teams maintain massive test suites without knowing which tests actually provide value.

The Cost:

Slow CI pipelines running thousands of low-value tests. Maintenance burden from tests that don't protect anything. Investment in testing that doesn't improve quality.

4. Manual Quality Processes That Don't Scale at AI Speed

AI tools accelerate code generation 10x. But test quality processes haven't evolved. Teams manually review test results, manually investigate flaky tests, manually compare local and CI environments. The gap between code velocity and quality assurance grows daily.

The Cost:

AI-generated code ships with AI-assumed quality. Technical debt accumulates faster than teams can address it. Quality becomes the bottleneck to AI-enhanced velocity.

The Obvyr Solution: Comprehensive Data + Pattern Recognition

Obvyr transforms testing from assumption-based to evidence-based through two core capabilities:

1. Comprehensive Test Execution Data Collection

Every test run. Every environment. Every developer.

• Local Development: Capture test runs from individual developer machines
• CI/CD Pipelines: Collect execution data from all automated builds
• Complete Context: Command, duration, output, environment, user, timestamp
• Full Coverage: Unit tests, integration tests, type checking, linting—any automated quality check

Unlike traditional testing tools that only show point-in-time results, Obvyr captures the complete history of test execution across your entire engineering organisation.

2. Pattern Recognition Over Time

Patterns reveal what snapshots miss.

• Flaky Test Detection: Identify tests that fail inconsistently by analysing execution patterns across hundreds of runs
• Environment Drift Analysis: Compare local vs. CI execution to expose systematic environmental differences
• Test Value Assessment: Distinguish high-value tests from noise based on failure patterns and coverage
• Trend Analysis: Spot degrading test quality before it becomes a production incident

Traditional tools show you "test passed" or "test failed." Obvyr shows you why tests fail, when they fail, and what that means for your deployment confidence.

The Four Key Differentiators

1. Comprehensive Data Collection: Every Test Run Captured

Most tools sample test results. Obvyr captures everything:

• Every test run from every developer's machine
• Every CI/CD pipeline execution
• Every environment (local, staging, production)
• Every test type (unit, integration, E2E, linting, type checking)

Why it matters

Patterns only emerge from comprehensive data. Missing data means missing insights. Sporadic collection misses the systematic issues that cause production incidents.

2. Pattern Recognition: Trends Over Point-in-Time Snapshots

Coverage reports and test results show you one moment in time. Obvyr analyses patterns across thousands of executions:

• Flakiness: Is this test truly broken or inconsistently failing?
• Velocity: Are tests getting slower over time?
• Reliability: Which tests have never failed? Which fail frequently?
• Environment: Do failures correlate with specific machines, users, or environments?

Why it matters

A single test failure is data. A pattern of test failures is insight. Obvyr provides the latter.

3. AI-Era Relevance: Disciplined Testing at AI Development Speeds

AI tools like GitHub Copilot and Claude accelerate code generation by 10x. But they don't automatically improve test quality. Teams need disciplined testing practices that scale at AI speeds:

• Rapid Validation: Quickly assess whether AI-generated code has AI-reliable tests
• Systematic Analysis: Pattern recognition reveals test quality issues faster than manual code review
• Quality Guardrails: Evidence-based testing ensures AI velocity doesn't compromise reliability

Why it matters

AI makes it easier to write code. Obvyr makes it possible to trust that code.

4. Environment Visibility: Local vs. CI Exposes Systematic Issues

"Works on my machine" shouldn't be a meme—it should be impossible. Obvyr compares local and CI execution to reveal:

• Configuration Drift: Different environment variables, dependencies, or system settings
• Timing Issues: Race conditions that only appear under CI load
• Data Differences: Test data that exists locally but not in CI (or vice versa)
• Infrastructure Gaps: Network behaviour, file system differences, or resource constraints

Why it matters

Most production incidents trace back to environmental differences that traditional testing doesn't reveal.

The Transformation: From Assumption to Proof

Before Obvyr

Assumption-Based Testing:

• "Our tests are probably reliable because they usually pass"
• "Coverage is 85% so we're probably protected"
• "It works locally so it should work in CI"
• "The test suite is slow but we assume it's all necessary"

Result

Deploy with crossed fingers. Debug production issues that "passed all tests." Maintain test suites without understanding their value.

With Obvyr

Evidence-Based Testing:

• Prove reliability: "These 847 tests have never failed in 12,000 executions across all environments"
• Prove coverage: "These 23 tests protect our critical payment flow and catch 94% of payment-related bugs"
• Prove consistency: "Local and CI environments match on 99.7% of test executions; here are the 3 systematic differences"
• Prove value: "These 412 tests account for 78% of CI time but have never caught a bug—candidates for removal"

Result

Deploy with confidence. Prevent production issues by understanding test patterns. Optimise test suites based on evidence, not assumptions.

Real Value Delivered

For Individual Developers

• Faster Feedback Loops: Know immediately if a test failure is flaky or real
• Reduced Debugging Time: Pattern insights point to root causes, not just symptoms
• Deployment Confidence: Evidence-based assurance that your code is ready

For Engineering Teams

• Improved Test Quality: Systematic identification and resolution of flaky tests
• Optimised CI/CD: Remove low-value tests, keep high-impact tests, reduce pipeline time
• Better Collaboration: Shared visibility into test execution patterns across the team

For Engineering Leaders

• Quality Metrics That Matter: Move beyond coverage % to actual test effectiveness
• ROI Visibility: Understand testing investment vs. quality outcomes
• AI-Era Readiness: Quality practices that scale with AI-accelerated development

For Compliance & Security Teams

• Audit Trail Evidence: Complete, immutable record of all test executions across your organisation
• Compliance Documentation: Automated evidence collection for regulatory requirements and customer audits
• Security Validation: Proof that security tests execute consistently across all environments
• Change Control Records: Historical verification of testing practices for governance requirements

Why Now? The AI Development Inflection Point

AI tools have fundamentally changed software development velocity. Code generation that took hours now takes minutes. But testing practices haven't evolved to match.

The Gap:

• AI accelerates code generation by 10x
• Manual testing processes remain linear
• Quality assurance becomes the bottleneck

The Risk:

• Fast code with assumed quality
• Test suites that grow without validation
• Production incidents from "AI-tested" code

The Obvyr Solution:

• Systematic test quality analysis at AI speeds
• Evidence-based validation of AI-generated code
• Disciplined testing practices that scale with AI development

Compliance and Governance Value

Beyond improving test quality and development velocity, Obvyr provides critical value for organisations with regulatory requirements or customer audit obligations.

Automated Audit Trail

The Challenge: Regulatory frameworks and customer audits require proof of testing practices. Manual documentation is time-consuming, error-prone, and difficult to maintain.

Obvyr's Solution: Every test execution is automatically recorded with complete context:

• Who ran the test (developer or CI system)
• When it was executed (timestamp)
• What command was run (full execution context)
• What the result was (pass/fail with complete output)
• Where it ran (local, CI, environment details)

Why it matters

Compliance audits require evidence, not assertions. Obvyr provides comprehensive, immutable records without manual documentation overhead.

Compliance Framework Support

Obvyr helps organisations meet testing-related requirements across multiple frameworks:

Quality Management Systems:

• Evidence of systematic testing practices
• Proof of regression testing execution
• Documentation of test coverage and effectiveness
• Historical records of quality assurance activities

Change Control Requirements:

• Verification that tests execute before deployment
• Historical comparison of test results over time
• Proof of environment parity validation
• Evidence of systematic quality gates

Security Compliance:

• Proof that security tests run consistently
• Environment configuration drift detection (security implications)
• Evidence of systematic security validation
• Test execution accountability and traceability

Provable Compliance

Rather than manually documenting testing practices for audits, Obvyr provides comprehensive evidence automatically collected during normal development workflows.

Customer Audit Readiness

Enterprise customers increasingly require evidence of rigorous testing practices. Obvyr provides:

For Security Reviews:

• Proof of security test execution frequency
• Evidence of environment parity validation
• Historical test reliability metrics
• Change control compliance records

For Quality Audits:

• Comprehensive test execution history
• Proof of systematic regression testing
• Evidence of test effectiveness (not just coverage)
• Documentation of quality improvement over time

Risk Mitigation

Deployment Evidence: Prove that tests executed successfully before production deployment

Test Integrity: Demonstrate that tests actually run (not just exist in the codebase)

Environmental Controls: Show systematic validation of environment parity

Change Validation: Provide evidence of testing at each change

Compliance Without Overhead

Obvyr collects compliance evidence as a by-product of normal development. No additional documentation burden, no manual record-keeping, no process disruption.

Getting Started

Ready to transform from assumption-based to evidence-based testing?

1. Understand the Problems - See detailed scenarios of how Obvyr solves specific testing challenges
2. Explore AI-Era Testing - Learn why testing insights matter more than ever in AI-accelerated development
3. Get Started - Set up your first project and start collecting evidence in 10 minutes
4. See the ROI - Understand the business value and return on investment

The choice is simple: Continue assuming your tests work, or start proving it.

Next Steps

Ready to prove your test reliability? Head to our Getting Started guide to begin collecting comprehensive test execution data in minutes.