SaaS Product
Organizational Development
The FairWorx Initiative™ helps organizations build fair, inclusive, and health-conscious workplaces by combining the speed of AI with expert consultant oversight. The FairWorx platform evaluates over 200 metrics through employee surveys, policy reviews, and internal data analysis, delivering a comprehensive view of organizational equity. The reports generated enable companies to identify gaps in human capital, improve employee welfare, and turn workplace fairness into an ethical and competitive advantage.
We worked with the FairWorx team in an agile process to define MVP features, design prototypes and build a system that could manage complex workflows. We followed a complete 0-to-1 approach, including extensive research, user-centered design, full-stack development, and AI prompt engineering.
Interviewed key stakeholders and FairWorx consultants to identify business goals and user needs that help drive user-centered design decisions.
Continuous refinement of user flows reviewed with FairWorx consultants to optimize the complex workflows and ensure insightful outputs.
Modern AI-enabled full-stack app with React for dynamic front-end, Python for scalable back-end, and APIs integrated with OpenAI running on AWS.
Connected AI capabilities with expert insight to prevent inaccuracies and generate consultant-ready analysis with minimal manual input.
To meet the goals of efficiency, accuracy, and insight, we developed an AI-powered platform that blends automation with expert oversight, streamlining complex audits while preserving the human element of equity analysis. The solution was designed around five specialized features: Document Review, Report Analysis, Organizational Profile, Employee Survey, and Dynamic Reports.
The Document Review feature automates the analysis of 28 organizational policy documents, including critical areas such as anti-discrimination and harassment, hiring and promotion, and professional development. Each document is evaluated using a set of risk indicators developed by FairWorx consultants. These documents are then graded against rubrics also created by the consultants, ensuring a consistent, expert-informed standard of assessment across all document types.
During the document analysis workflow, consultants review a list of AI-detected risks and decide whether to accept or dismiss them. Each risk is supported by AI-generated reasoning, pre-populated with two editable fields: Issue, explaining why the content was flagged, and Suggestion, offering guidance on how to improve it. We introduced risk grouping for repeated misuse of the same word or phrase across a document. This approach enhances clarity, speeds up decision-making, and ensures users retain full editorial control.
In the Report Analysis, the platform processes 9 internal organizational reports, such as employee salary tables, complaint management system outputs, and demographic data. AI is used to extract and structure the data efficiently, but all outputs need to be reviewed and confirmed by FairWorx consultants. This consultant-led approach allows users to add comments, make contextual adjustments, and ensure the results reflect the realities of the organization. The system also compiles historic company data to reveal trends over time that indicate growth or decline.
The Employee Survey is distributed via SurveyMonkey, allowing the team to collect firsthand perspectives from employees. This survey captures how policies impact daily work life and provides space for individuals to self-identify within more specific demographic categories. The survey results are cross-referenced with internal policies and reports to compare the vision of the organization to the actual experiences of its employees.
To improve the quality and reliability of AI-generated outputs, we employed advanced prompt engineering techniques beyond standard Retrieval Augmented Generation (RAG). These included zero-shot and few-shot contextual scaffolding, dynamic prompt chaining based on report types, and role-based conditioning to guide the AI in adopting the appropriate analytical tone (e.g., consultant vs. executive summaries). This approach significantly reduces hallucinations, false positives, and misinterpretations of sensitive internal data. Prompt templates were also modularized to adapt to variances in organizational reporting styles, improving the precision of insight extraction.
The platform generates 6 detailed, interactive reports: Employee Demographic Overview, Retention Intention, Pay Equity, Professional Development, Workplace Stress, and Leadership. These reports synthesize data across more than 200 metrics to support FairWorx consultants in their analysis. The reports are carefully calibrated to serve both technical consultants who need rich, granular data and executives who need concise, strategic insights to inform decision-making.
Each report combines high-level visualizations with interactions that enable FairWorx consultants to cross-reference data sources and explore deeper demographic trends. A side-by-side view of the same data gathered from multiple sources allows the consultant to identify discrepancies to highlight inaccurate data. The tool also provides more detailed demographic data to identify specific racial/ethnic groups that may be underrepresented in the broader categories.
The new platform transformed FairWorx’s equity audit process by reducing analysis time from three months to just weeks, while increasing the depth, clarity, and accessibility of insights.
By automating manual tasks and generating insight reports, it allows consultants to focus on interpretation and strategy rather than identification and documentation.
Executive teams now receive clear, actionable reports to inform meaningful policy changes, and the platform’s scalability has empowered FairWorx to support more organizations efficiently, elevating both operational impact and the strategic value of workplace fairness.
