Ship faster with CI you can actually trust
Flaky tests waste 4+ hours per developer per week. They block merges, erode trust, and slow delivery to a crawl. Drape detects flaky tests, suppresses false negatives, enforces coverage guardrails, and gives your team and AI agents the context to decide what to fix — so your pipeline stays green and your team ships.
14-day free trial. No credit card required.
Works with your stack
From broken build to shipped fix — automatically
Drape doesn't just show you what's wrong. It suppresses false negatives, blocks coverage regressions, and gives your team and AI agents the context to decide what to fix next.
Discover
Know in seconds whether a failure is a real bug, a flake, or a CI environment issue
Flaky Test Detection
Automatically score and flag flaky tests so your team stops chasing phantom failures.
| test_login | ||||||
|---|---|---|---|---|---|---|
| test_checkout | ||||||
| test_api | ||||||
| test_export |
Test Health Grid
Every test, every commit. Scattered red means flaky. Solid columns mean a CI environment issue. Patterns jump out instantly.
AI Failure Classification
Automatically triage every failure — real bug, flaky test, or CI environment issue — so developers stop wasting time reading logs.
Fix
Enforce quality without blocking on false negatives
Test Suppression
Automatically suppress flaky test failures so they stop blocking merges — with SLAs and fix tickets to ensure nothing gets swept under the rug.
Agent-Ready Context
Give AI agents structured failure context, flakiness history, and coverage gaps so they can help your team decide what to fix.
Prevent
Automated guardrails that block regressions at the PR
Coverage That Only Goes Forward
Enforce line-level coverage. Block PRs that drop coverage on changed files — no more gaming percentage targets.
Drape · PR #142
⚠️ 3 lines lost coverage in middleware.py
🆕 New flake: test_login_timeout
🐌 test_export 3.2x slower
PR Insights
Drape posts actionable context on every PR: new flakes, coverage regressions, and duration spikes — before the code merges.
Container CVE Tracking
Ingest SARIF scans from Grype or Trivy. Block PRs that introduce new critical vulnerabilities. Enforce SLA-based fix timelines by severity.
# ci.yml
curl -X POST drape.io/api/v1/upload \
-F "file=@results.xml"
Zero SDK. Zero Lock-in.
Standard JUnit XML, SARIF, Cobertura, LCOV, and Go coverage. No SDK, no proprietary uploader, no vendor lock-in.
Everything ratchets forward
Drape baselines your current state and blocks regressions on every PR — for coverage, security, and code quality. You don't have to fix everything overnight. You just have to stop making it worse.
Container CVE Tracking
Ingest SARIF from Grype, Trivy, or any container scanner. Diff CVEs against baselines on every PR. Enforce SLA-based fix timelines by severity — critical vulnerabilities never slip into production unreviewed.
Code Quality That Only Goes Forward
Ingest SAST and lint results via SARIF from Semgrep, ESLint, golangci-lint, and more. Baseline your current state, block new violations on every PR, and ratchet toward zero — incrementally, without stopping the world to fix everything at once.
Drape · PR #287
⚠️ 3 lines lost coverage in middleware.py
🚨 1 new critical CVE: CVE-2026-1234
🚫 2 new Semgrep findings in auth.py
🆕 New flake: test_login_timeout
Unified PR Insights
Tests, coverage, CVEs, and lint results — one PR comment, one decision point. Everything your team needs to ship with confidence, without switching tools.
Reliable CI in 5 minutes
Connect your repository
Install the GitHub App or add a GitLab webhook. One click.
Upload your CI data
Add one line to your CI config. We ingest JUnit XML for tests, SARIF for security scans and lint results, and Cobertura/LCOV for coverage — no SDK, no vendor lock-in.
# .github/workflows/ci.yml
- name: Upload to Drape
run: |
curl -X POST https://drape.io/api/v1/upload \
-H "Authorization: Bearer $DRAPE_TOKEN" \
-F "file=@results.xml"
-F "file=@grype-report.sarif"
Drape takes action
Flaky tests get suppressed. Coverage regressions and new CVEs get blocked. Lint violations get tracked. AI agents get the context to help fix what matters. Your team ships.
Built for the agentic coding era
AI coding agents generate code at scale — but when tests fail, they're flying blind. Drape gives agents structured context to help diagnose test failures and decide what to fix.
The problem
AI agents generate code, but when tests fail, they're flying blind. They don't know which tests are flaky, what the historical failure pattern looks like, or whether a coverage regression is real. Without that context, agents retry blindly or punt the problem back to a human.
How Drape closes the loop
- Failure context via API — agents know if a failure is a flake, a real bug, or infra
- Historical patterns — agents see which tests fail intermittently vs. consistently
- Root cause data — stack traces, error patterns, and affected lines surfaced for agent consumption
- Coverage guardrails — agents know exactly which lines need tests before a PR can merge
- Security context — agents see new CVEs and lint violations introduced by a PR
- MCP integration — connect Drape to Claude Code, Cursor, and other agentic tools