High-performance AI without the risks.
Services
If you are a VC, an accounting firm, a non-for-profit, or an organization with clients that would benefit from a preferred partnership, we would love to connect with you. Inquire here.
Eticas.ai is a leading global SaaS company specializing in AI auditing, bias monitoring, and certification, with over a decade of experience helping EU and US organizations optimize their AI processes, leading to better, safer, and fairer business decisions.
Our End to End Solution
Bias Beyond Protected Attributes
In our experience, outlier attributes that lead to unfair discrimination dynamics are not limited to protected attributes. We understand complex social dynamics and build our knowledge into our data.
Pre & Post Processing
Eticas performs end-to-end audits that leverage performance metrics with contextual data (demographic libraries) to assess systems in context. We differentiate between outputs and impacts to provide true insight into the societal impact of a system.
Continuous Monitoring
Eticas audits are not a one-off inspection. We establish the relevant monitoring signals, metrics and benchmarks and track them on a regular basis.
Personalized Offerings
We tailor our audits to the specific characteristics of AI systems, differentiating between different AI systems as data availability and impact vary depending on the situation.
Documentation
Documentation is a key challenge when auditing. We work with clients to ensure that our audits cover pre-processing decisions and data and provide tools for best practices
Audited AI Certification
Our "Audit certification" serves as an external validation, showcasing audited companies as trusted leaders committed to ethical practices. To qualify for Eticas Certification, we conduct periodic reviews and cross-reference data sets with our robust geo-sociographic database.
Pre-Processing Bias Risk
0%
Techno-solutionist
0%
Data Availability / Scarcity
0%
Historical
0%
Labeling
0%
Outliers
0%
Selection / Population / Survey
0%
Sampling / generalization
In-Processing Bias Risk
0%
Measurement
0%
Hot hand and gambler’s fallacy
0%
Aggregation
Post-Processing Bias Risk
0%
Benchmark test
0%
Data visualization
0%
Automation
0%
Accessibility
General Fairness Score
0%