Embracing Responsible AI

Fractal's enablers

Codebase Scalable custom codes with user-friendly APIs, full documentation, and endless customization options.

Chief RAI Empowering RAI adoption with a taskforce for unified organizational integration and auditability

Education Comprehensive RAI education for all levels, disciplines, and domains – technical and strategic




Adoption Empowering developers with actionable checklists for ethical, fair, transparent, accountable, and private ai system

ESG Diagnostic Calculating carbon emissions, minimizing environmental impact, and optimizing technological resources

Synthetic data Privacy by design and synthetic data for ethical, secure, and accountable practices

Fractal offers maturity assessments to evaluate clients' current standing regarding RAI practices and propose tailored solutions accordingly. From initial As-Is and To-Be assessments to in-depth diagnosis, we aim to foster collaboration and closely partner with organizations to incorporate RAI strategies into their systems.

To ensure RAI compliance, our certification process involves assessing projects using over 50 qualitative and quantitative criteria. Only after meeting these requirements is a project declared as RAI compliant.

RAI Certification Process Flow

Align on RAI definition and business objective

Share project RAI summary, NPS and record learnings for future use

Share model building outcome – an update on fairness and explainability assessment as appropriate

Data Lifecycle

Model Deployment

Project Kick Off

Business Definition

Model Development

Project Closure

Complete model documentation, audit trail, RAIchecklist process and conduct an audit

Deliver a RAI report on data and highlight any privacy or PII/safety risks as applicable

Share a detailed explanation of the Fractal RAI Certification process

© 2023 Fractal Analytics Inc. All rights reserved


Made with FlippingBook - PDF hosting