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.

Arise Reinforced Learning Results

Turnaround SLA

hour average task completion
0

Accuracy

first‑pass accuracy (< 0.3% rework rate)
0 %

First‑Pass Yield

tasks completed without manual corrections within first 2 weeks
0 %

Upsell

Offered on 99% of orders
0 %

Automation

repeatable work handled by optimized workflows
0 %

Stakeholder Satisfaction

positive feedback on deliverables
0 %

Each brand has a unique CX need. Schedule a time to meet with our CX experts to learn how Arise can help.