Coming Soon

Find the bugs your
tests don't see.

Germanium connects formal system modeling with adaptive test generation, surfacing edge cases, null combinations, and rare interactions that escape traditional testing.

Bug Found

Null email + OAuth login → crash at auth_service:247

Traditional tests: 0 / 147 caught this

60k
Input combos in a 10-field form
40–60%
Fewer test runs needed
2
Integrated components
The problem

Your tests only cover the paths
you've thought of.

Combinatorial explosion

A form with 10 fields and 3 states each creates 60,000 combinations. No one can test this manually.

Documentation drift

Architecture diagrams get stale. Developers hold system knowledge in their heads. Testing proceeds from outdated assumptions.

Unknown unknowns

Traditional tests verify what you think to test. They can't discover the edge cases you haven't encountered yet — the ones that only appear in production.

The Solution

Two components. One closed loop.

System knowledge drives smarter tests. Smarter tests improve system knowledge.

Component 01

System Modeling

Capture your architecture accurately through guided wizards, code analysis, or existing diagrams. Define data contracts, interaction patterns, and expected behaviors.

  • Gherkin behavioral specs
  • API data contract definitions
  • PlantUML, Mermaid, Jira export
  • User journey maps
Component 02

Adaptive Test Generation

Bayesian optimization learns which test strategies find bugs most efficiently, concentrating effort where it matters and abandoning unproductive paths quickly.

  • Bayesian multi-armed bandit optimization
  • AI-powered failure pattern recognition
  • Language-agnostic
  • Natural language bug explanations
Capabilities

Built for real engineering teams.

Cost-efficient by design

Adaptive exploration reduces test execution costs by 40–60% vs. exhaustive approaches, concentrating budget where it discovers the most bugs.

Learns your codebase

The Bayesian model accumulates institutional knowledge across sessions. Testing gets not only more thorough but also smarter.

Zero noise in the output

Failure clustering deduplicates findings. Users receive minimal reproduction cases and plain-English explanations instead of thousands of overlapping reports.

Works with your stack

Language-agnostic by design. Tests at the API contract level so it works with Python, Java, Go, Node, or anything else.