Detail: Bug finder for detecting issues in application backends.

What it does

Detail scans application codebases to identify bugs, security vulnerabilities, data loss risks, and billing errors. The tool exercises code paths automatically, flags issues it finds, and can generate pull requests to fix them. Users set it up in under five minutes and get results within the first week free.

Who it is for

The product targets software teams shipping features at speed, particularly those using modern development practices like agent-based workflows or rapid deployment cycles. It works on backend systems and has been used by engineering teams at companies like Notion, Vanta, Semgrep, and SavvyCal.

Pricing

The site does not show prices.

How it stands out

Detail claims to detect bugs that slip past code review and other automated tools. According to user testimonials, it finds issues competitors miss—teams running multiple PR agents and pen testing solutions report that Detail's scans still surface additional problems. The product filters results to show the top 1% of findings most likely to matter, addressing signal-to-noise concerns common in automated analysis tools. Its ability to generate fixes via pull requests means developers can merge corrections without manual remediation.

The founding team began by tackling technical debt broadly but found bug detection was a better fit for AI-driven automation. They positioned the product as a complement to human code review rather than a replacement.

What a founder should check

An entrant should verify how Detail's detection depth compares to static analysis tools like Semgrep, which already serve many of the same customers. Switching costs matter: teams that have tuned existing linters and security scanners may resist adding another vendor. Finally, explore whether the moat holds at scale. As competitors add AI-powered bug-finding to their platforms, Detail would need to either deepen detection quality, expand into adjacent problems like performance optimization, or entrench through integrations and historical data that make it harder to replicate results elsewhere.

Thinking of building something like this?

Every launch here is a competitor to somebody's idea. If yours is close, check it against the market before you build: the Full Check names the rivals, the prices and the gaps.