Build comprehensive evaluation and safety frameworks for AI agents. Access open-source eval protocols, safety testing frameworks, and risk assessment tools to ensure safe and reliable AI agent deployment.
Organizations building, deploying, or managing AI agents who need comprehensive evaluation and safety frameworks. Ideal for AI engineers, ML teams, and organizations deploying autonomous agents where safety and reliability are critical.
70-90% fewer incidents
Comprehensive safety testing identifies and mitigates risks before production deployment
60-80% faster
Standardized evaluation protocols reduce testing time and improve consistency
100% coverage
Comprehensive evaluation frameworks ensure regulatory compliance and audit readiness
85-95% accuracy
Rigorous evaluation and safety testing improve agent performance and reliability
Comprehensive evaluation protocols and testing frameworks for AI agents. Standardized test suites covering accuracy, reliability, safety, and performance. Benchmark datasets and evaluation metrics for consistent testing
Safety testing frameworks to identify risks, vulnerabilities, and failure modes. Adversarial testing protocols, robustness testing, and edge case identification. Risk assessment methodologies and safety scoring systems
Comprehensive evaluation metrics covering accuracy, latency, cost, safety, and reliability. Industry benchmarks and performance standards. Customizable metrics based on use case and requirements
Risk assessment tools and methodologies for AI agent deployment. Risk scoring frameworks, threat modeling, and vulnerability assessment. Compliance checklists and audit frameworks
Implementation guidance and best practices for deploying evaluation frameworks. Integration support with existing testing infrastructure. Training and documentation for evaluation teams
Access open-source evaluation protocols and safety frameworks. Customize frameworks for your specific agents, use cases, and requirements. Select evaluation metrics and benchmarks relevant to your deployment.
Implement evaluation protocols in your testing infrastructure. Run comprehensive safety and performance tests. Conduct risk assessments and vulnerability testing. Generate evaluation reports and safety scores.
Establish ongoing evaluation and monitoring processes. Continuously test and validate agent performance. Update frameworks based on new risks and requirements. Maintain compliance and audit readiness.
4-8 weeks
From framework selection through implementation, testing, and validation. Ongoing evaluation is continuous
3-5 hours/week
AI engineering team time for framework customization, test implementation, and evaluation execution
Timeline factors:
Open-source + implementation support
Open-source frameworks are free. Implementation support and customization services: $15K-$50K for framework implementation and integration. Ongoing evaluation support: $5K-$15K/month for continuous testing and monitoring.
Our evaluation and safety frameworks directly impact AI agent reliability, safety, and compliance metrics.
Agent accuracy (%)
Agent reliability (%)
Safety incident rate (#)
Evaluation cycle time (days)
Test coverage (%)
Risk score
Compliance rate (%)
Agent failure rate (%)
Evaluation cost per agent ($)
Time to evaluation (days)
Safety test pass rate (%)
Agent performance score
We provide open-source frameworks and protocols that integrate with your existing testing and monitoring infrastructure. Frameworks are language-agnostic and work with common AI platforms.
Risk: Evaluation frameworks may not cover all risks, edge cases, or failure modes, leading to undetected issues in production
Safeguard: We provide comprehensive evaluation protocols covering multiple dimensions (accuracy, safety, reliability, performance). We include adversarial testing and edge case identification. We offer customizable frameworks to address specific risks. We also recommend continuous evaluation and monitoring in production. We provide guidance on expanding test coverage based on use case.
Risk: Passing evaluation tests may create false confidence, but agents may still fail in production due to distribution shift or unforeseen scenarios
Safeguard: We emphasize that evaluation is necessary but not sufficient—production monitoring is critical. We provide frameworks for continuous evaluation and monitoring. We include distribution shift detection and production validation protocols. We also recommend gradual rollout and canary deployments. We provide guidance on interpreting evaluation results and setting appropriate confidence thresholds.
Risk: Evaluation frameworks may be too complex or difficult to implement, leading to low adoption or incomplete implementation
Safeguard: We provide clear documentation, implementation guides, and best practices. We offer implementation support and customization services. We design frameworks to be modular and adaptable. We also provide training and workshops for evaluation teams. We offer simplified versions for teams getting started and advanced features for mature organizations.
Challenge: FinTech company deploying AI agents for customer service and fraud detection needed comprehensive safety and compliance evaluation. Lacked standardized testing protocols and risk assessment frameworks. Regulatory requirements demanded rigorous evaluation and audit trails. Experienced agent failures in production due to insufficient testing.
Solution: Implemented comprehensive evaluation and safety framework. Deployed open-source evaluation protocols customized for financial services use cases. Conducted safety testing including adversarial testing and edge case identification. Established risk assessment and compliance checklists. Integrated evaluation into CI/CD pipeline for continuous testing.
Impact: Reduced safety incidents by 85% through comprehensive testing. Achieved 100% compliance coverage with regulatory requirements. Improved agent reliability from 75% to 92% through rigorous evaluation. Reduced evaluation time by 60% with standardized protocols. Passed regulatory audits with comprehensive documentation. ROI: $300K value from avoided incidents, compliance, and improved reliability.
Challenge: Healthcare organization deploying AI agents for clinical decision support needed rigorous evaluation and safety testing. Patient safety requirements demanded comprehensive testing. Lacked evaluation protocols and safety frameworks. Needed to demonstrate safety and reliability to clinical teams and regulators.
Solution: Implemented comprehensive evaluation and safety framework with healthcare-specific protocols. Conducted safety testing including accuracy validation, edge case testing, and failure mode analysis. Established risk assessment and safety scoring. Created evaluation reports and documentation for regulatory submission. Integrated evaluation into development and deployment workflows.
Impact: Achieved 95%+ agent accuracy through rigorous evaluation. Reduced safety concerns and gained clinical team confidence. Passed regulatory review with comprehensive safety documentation. Improved agent reliability from 80% to 94%. Reduced evaluation time by 50% with standardized protocols. ROI: $500K+ value from improved patient safety, regulatory compliance, and clinical adoption.
Service #30 provides open-source frameworks and protocols that you implement yourself, while Service #7 provides ongoing evaluation services where we run tests for you. Service #30 is ideal if you want to build internal evaluation capabilities, while Service #7 is ideal if you want to outsource evaluation. Many clients use both—Service #30 for framework and Service #7 for ongoing testing.
Yes, core evaluation protocols and frameworks are open-source with permissive licenses (typically MIT or Apache 2.0). You can use, modify, and distribute them freely. Some advanced features or specialized protocols may have different licensing. We provide clear licensing information for all components. Implementation support and customization services are separate from open-source frameworks.
We provide evaluation coverage guidelines and best practices. We recommend testing across multiple dimensions: accuracy, safety, reliability, performance, and edge cases. We offer evaluation audits to assess your current coverage and identify gaps. We also provide frameworks for risk-based testing prioritization. Most importantly, we emphasize that evaluation is an ongoing process, not a one-time activity.
Yes, frameworks are designed to be customizable. We provide modular components that you can adapt for your specific agents, use cases, and requirements. We offer implementation support and customization services to help you tailor frameworks. We also provide best practices and examples for common customization scenarios. Many organizations customize frameworks for industry-specific requirements (healthcare, finance, etc.).
Frameworks are designed to integrate with common testing infrastructure. We provide APIs and integrations for CI/CD pipelines, testing frameworks, and monitoring platforms. We offer implementation support to help with integration. We also provide examples and documentation for common integration scenarios. Most organizations integrate evaluation into their existing development and deployment workflows.
We offer implementation support and customization services. We can help you select appropriate frameworks, customize them for your needs, and integrate with your infrastructure. We provide training and workshops for evaluation teams. We also offer ongoing support for framework updates and best practices. Many clients start with implementation support and then maintain frameworks internally.
Typical ROI is 5-10x within the first year. For example, if you avoid one major agent failure incident ($100K+ cost), that alone pays for implementation. Reduced safety incidents, improved reliability, and compliance benefits provide ongoing value. Most clients see payback within 2-3 months from avoided incidents and improved reliability. Open-source frameworks have no licensing cost, so ROI is primarily from implementation support and avoided risks.
Let's discuss your evaluation needs and explore how our open-source frameworks can ensure safe and reliable AI agent deployment.
For ongoing evaluation services where we run tests for you. Perfect complement to evaluation frameworks—use frameworks for structure and our services for execution.
Build dashboards and monitoring systems to track agent performance in production. Perfect complement to evaluation frameworks for continuous monitoring.
Last updated: November 2025