deep-dev.com

What It Is

Deep Dev positions itself as a production intelligence and trust layer for “AI-built software.” Its core goal is to connect source code, builds, previews, runtime logs, and reports into a single evidence chain before software is shipped. It is not just a standalone static scanner. After connecting to GitHub, it runs security, code, build, and log checks against real repositories, then uses AI synthesis to produce a clear verdict covering risk level, confidence, evidence, and prioritized fixes.

Core Capabilities and Ecosystem

In terms of functionality, Deep Dev covers GitHub connection, unsafe pattern scanning, dependency risk checks, workflow issues, secrets, error-prone generated code, and running install/build commands inside isolated workers. Build Lab can capture static artifacts and live preview snapshots. On the logging side, it supports Railway, Vercel, or pasted generic logs, turning noisy failures into likely causes and suggested next actions. Reporting features include branded pages and PDF export, making it suitable for team or client delivery scenarios. Supported languages and frameworks are not listed in the main content, and no API/SDK details are disclosed, which may affect evaluation for more complex engineering stacks.

Pricing and Deployment

Pricing is subscription-based, with a 14-day Team trial available. Builder costs $29/month and is aimed at individuals or early-stage teams, including 3 repositories, 50 scans, and 120 build minutes. Team costs $149/month, increasing limits to 25 repositories, 500 scans, and 1000 build minutes, with support for runtime log ingestion. Scale is custom-priced and includes custom limits, private runners, and priority support. The main content does not state whether the product is open source or whether full self-hosting is available; only private runners are mentioned for the enterprise plan.

Pros, Cons, and Who It’s For

Its main strength is that it unifies deterministic checks, build evidence, logs, and AI summaries into actionable reports, reducing the effort teams spend piecing together conclusions from multiple scanning tools. Tenant-level workspaces and data boundaries also make it suitable for multi-client work or team collaboration. The drawbacks are the lack of public information on language/framework coverage, rule coverage, APIs, data retention, compliance details, and accessibility from China. The terms of service also make clear that AI verdicts are only decision-support aids and do not guarantee security, compliance, or defect-free software. Deep Dev is best suited for software teams using AI coding tools that need pre-release risk review, build validation, and client-facing reports.

China Access and Alternatives

The collected content does not provide information on network connectivity from mainland China, payment methods, or localization support, so china_access can only be marked as unknown. If access or payment is limited, alternatives to consider depending on needs include SonarQube/SonarCloud, Snyk, Semgrep, GitHub Advanced Security, or building a custom delivery-check workflow by combining Sentry, Datadog, and Vercel/Railway logging capabilities.