Build trustworthy software agents with measurable quality and code ROI.
Evaluate code syntax, security flaws, algorithm efficiency, and multi-step logic. OpenVals helps engineering teams prevent insecure code generation, cut debugging cycles, and verify code agent trust.
Trust Score Preview
What you get.
Clear, evidence-backed deliverables for technical teams, leadership, customers, and auditors.
Execution Testing
Compile and run model code outputs to measure syntax, execution correctness, and logic.
Vulnerability Scanning
Audit generated code for security issues, prompt injections, and credentials leakage.
Logic Optimization
Measure code complexity, scalability, and algorithmic efficiency for maximum ROI.
Engagement workflow.
Ingest
Feed code challenges or system architectures into the engine.
Run
Verify code execution correctness, syntax, and computational cost.
Scan
Run static analysis and OWASP security vulnerability audits.
Grade
Report efficiency scores, execution success rates, and trust levels.
Start with the right level of AI assurance.
Enterprise AI Validation
A deeper evaluation of model quality, safety, reliability, bias, and deployment readiness.
- Model validation report
- Benchmark comparison
- Executive risk summary
AI Security
Manual and automated pressure testing for jailbreaks, prompt injection, leakage, and abuse cases.
- Attack findings
- Severity-ranked issues
- Mitigation playbook
Compliance Readiness
Evidence, controls, and governance artifacts for teams preparing for AI oversight.
- Compliance gap map
- Control checklist
- Audit-ready documentation
Book Your AI Trust
Get a fast baseline of your model's reliability, safety, compliance, and deployment risk before you invest in a full validation program.