Scaling Reasoning in the age of AI
Symbolic execution that finds bugs today — and teaches AI to find them tomorrow.
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> cc_queue_new at line 11.Why ?
Reliable
86.9% pass rate across Kani and Miri test suites. Real bugs found in hashbrown, Collections-C, and more.
LLM Synergy
19+ pp improvement in violation detection. Just ~3,000 traces needed to outperform a 4× larger model.
Fast
15.8× faster than CBMC. Analyze large codebases in minutes — sometimes seconds.
Comprehensive Coverage
Memory safety, overflow, data races, reachability — detected across Rust and C.
Formal verification × AI
LLMs approximate reasoning about code. Soteria makes it exact.
Verify what LLMs write
Catch memory bugs, overflows, and undefined behavior in AI-generated code before it reaches production — automatically, with full symbolic path coverage.
Improve how LLMs reason
Soteria's symbolic execution traces are proven training signal. Published research shows 19+ pp improvement in violation detection with just ~3,000 traces.
Built on peer-reviewed research from Imperial College London and Amazon Web Services.
See how AI teams use Soteria
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