How We Use AI

RAVES uses artificial intelligence and machine learning across multiple platform modules to improve efficiency, automate repetitive tasks, and surface actionable insights. AI is not a bolt-on feature — it is woven into the core of how RAVES works, under the umbrella of RAVES Intelligence™.

AI capabilities in RAVES are designed to assist human decision-making, not replace it. Final decisions — hiring, contract approvals, payments — remain with your team.

Our MatchIQ™ engine uses AI to match candidates to open roles based on skills, experience, availability, and historical placement outcomes.

• Candidate résumés and profiles are analysed to extract structured skills and seniority signals.
• Job descriptions are parsed to identify required and preferred competencies.
• Match scores are generated to rank candidates — these are advisory and can be overridden.
• Interview scheduling suggestions are generated based on availability patterns.
• No protected characteristics (race, gender, age, religion, disability) are used in matching logic.

RAVES AI monitors active contracts and work orders to surface financial and compliance risks in real time.

• Margin erosion alerts when bill rates drift relative to pay rates on a work order.
• Volume discount and rebate threshold notifications as milestones approach.
• Tenure-based incentive reminders when contract renewal windows open.
• Discrepancy detection between MSA terms and active work order line items.

Machine learning models trained on your historical timesheet data flag unusual entries before they progress to approval or payroll runs.

• Unusually high or low hours relative to a worker's established pattern.
• Duplicate timesheet submissions or entries spanning overlapping periods.
• Bill/pay rate mismatches on submitted timesheets vs. active work order terms.
• Late submission patterns that may indicate attendance or engagement issues.

RAVES AgentForce™ is our suite of autonomous AI agents that operate within your workflows:

• RIA (RAVES Interview Agent) — conducts structured AI-powered candidate screening interviews, scores responses, and produces summaries for recruiters.
• ROSS (RAVES Onboarding & Support Specialist) — guides new hires through onboarding steps, answers HR policy questions, and collects required documents.
• RAMA (RAVES Autonomous M2M Agent) — handles background API orchestration, data sync between integrated systems, and self-healing workflow retries.

RAVES AI models operate on data you and your workers enter into the platform. We do not use your data to train models shared with other customers.

• Workforce data: worker profiles, skills, employment history, and performance records.
• Operational data: timesheets, contracts, invoices, and approval histories.
• Interaction data: sequences of actions within the platform used to improve recommendations.
• No biometric data is collected or processed.
• Personal data used in AI processing is governed by our Privacy Policy and applicable law.

• All AI outputs are presented as recommendations — users always have the ability to accept, modify, or reject them.
• AI models are reviewed periodically for accuracy, fairness, and potential bias.
• Administrators can disable specific AI features per module in platform settings.
• AI processing complies with applicable data protection laws including GDPR and CCPA.
• We do not sell insights derived from your data to third parties.