Reinforced Learning & LLM Data Workflows
Challenge
Client: A leading AI-powered voice automation platform servicing quick‑service restaurants
Objective: Process high volume, fast turnaround annotation tasks to support AI order training—while maintaining best-in-class accuracy and automation.
Solution
Solution: Arise AI DataOps implemented an end-to-end generative-AI pipeline:
Prompt Engineering & Taxonomy: Transform real-time orders and raw voice transcripts into precise, structured annotation schemas for consistent model inputs.
Hybrid Annotation & QA: Leverage human-in-the-loop experts for labeling, with automated QA checks and rapid feedback to catch edge cases.
Adaptive Feedback Loop: Continuously retrain annotators on misclassifications and update taxonomies to refine model understanding.
24
Turnaround SLA
hour average task completion
99.7%
Accuracy
first‑pass accuracy (< 0.3% rework rate)
90%
First‑Pass Yield
tasks completed without manual corrections within first 2 weeks
99%
Upsell
Offered on 99% of orders
80%
Automation
repeatable work handled by optimized workflows
97%
Stakeholder Satisfaction
positive feedback on deliverables