From code change to verified release.

SAGOZEN automatically tests the application after a code change and gives the team evidence-based confidence about whether the change can be released.

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The Challenge

Why Traditional Approaches Fail

Passing CI unit tests don't guarantee a safe release. Teams lack multi-layer evidence connecting code changes to affected user journeys, API responses, and database mutations.

The SAGOZEN Solution

Evidence-Based Release Assurance

SAGOZEN Quality executes complete full-stack verification suites on private runners, collecting video, DOM, API, and DB evidence to output explicit PASS, REVIEW, or BLOCK release verdicts.

Core Solution Capabilities

Engineered capabilities designed to eliminate release friction.

PASS / REVIEW / BLOCK Release Gates

Every PR receives a verified verdict backed by multi-layer evidence rather than simple test pass counts.

Multi-Layer Evidence Inspector

Inspect video recordings, DOM tree snapshots, HTTP request payloads, and database mutations side-by-side.

AI Failure Triage & Root Cause Confidence

Automatically classifies failures into Product Bug, Environment Issue, Test Mismatch, or Flaky behavior with confidence scores.

Implementation & Configuration

Clean, standard execution scripts with zero vendor lock-in.

release-verdict.config.ts

typescript

import { defineReleaseGate } from '@sagozen/quality';

export default defineReleaseGate({
  targetEnv: process.env.PREVIEW_URL,
  verdictPolicy: {
    blockOnProductBug: true,
    reviewOnFlakyTest: true,
    minConfidenceScore: 0.90,
  },
  evidenceCollection: ['video', 'dom', 'network', 'db-mutation'],
  runner: 'self-hosted-k8s'
});

Frequently Asked Questions

What makes a SAGOZEN release verdict different from standard CI status?

Standard CI only says 'test failed'. SAGOZEN connects code changes to affected journeys, API responses, DB state, classifies the failure (e.g. 96% product bug confidence), and issues a clear PASS/REVIEW/BLOCK verdict.

Does AI Release Verification replace our QA team?

No. AI removes the repetitive manual bottleneck by executing scripts and analyzing evidence, while QA leads and managers keep quality ownership and final release approval.