Agentic AI and Accuracy

Agentic AI and Accuracy

Agentic AI, driven by advanced Large Language Model (LLM) technology, represents a transformative leap forward in customer experience (CX). However, fully harnessing its capabilities requires effectively addressing accuracy—a challenge that extends beyond the widely discussed "hallucination" issue. Retrieval-Augmented Generation (RAG) techniques and guardrail prompting have largely resolved hallucinations, yet accuracy remains quite a difficult problem. This article explores Crescendo’s distinctive approach to achieving and maintaining exceptional accuracy and reliability with Agentic AI.

Why Agentic AI?

Traditional customer service AI relies on rigid, scripted workflows, limiting flexibility, customer experience quality, and cost-effectiveness. Agentic AI overcomes these constraints, handling a broader variety of interactions with significantly reduced programming and operational expenses.  By reducing the cost of deploying CX automations, Agentic AI enhances your team’s productivity, boosting customer satisfaction and lowering overall expenses.

Accuracy: The Central Challenge

Agentic AI’s autonomous capabilities introduce unique accuracy challenges. Crescendo addresses these by leveraging deep operational expertise from managing large-scale CX operations involving thousands of human agents. In 2024, Crescendo took an innovative step for an AI company by acquiring PartnerHero, a prominent BPO organization. This novel strategy provided unmatched insights into scaling customer service operations and this is Crescendo’s differentiated advantage in refining Agentic AI accuracy.

Even in top-tier human-operated customer service, mistakes occur in more than 2% of interactions. Through rigorous operational practices, Crescendo has adapted proven human-quality management methods to achieve 99.8% accuracy in Agentic AI, representing a 10x improvement over human performance in knowledge and procedural accuracy.

Proven Approach to Accuracy

Crescendo's technology journey began in 2023 using OpenAI's GPT-3.5 for automated quality assurance in evaluating human agent interactions. Recognizing AI’s potential, Crescendo evolved to directly apply these quality-assessment methods to Agentic AI solutions.

Crescendo's operational leaders integrate AI-and-human outcomes, focusing exclusively on achieving superior customer experience. They utilize tools like Predicted CSAT (P-CSAT) scores and automated quality assessments to continually enhance both human and AI-driven performance. Feedback from these processes informs targeted adjustments by Crescendo’s AI Deployment Engineers (AIDEs).

Precision in Policy and Knowledge Content

Precise knowledge content and policy instructions are foundational to Agentic AI success. Unlike legacy AI solutions dependent on big data and extensive examples, Agentic AI thrives on clearly structured, factual, and policy-driven information. Excessive examples can cause inconsistent performance, complicating quality assurance.

Recognizing this, Crescendo developed specialized Agentic AI services for automated ingestion and refinement of knowledge content. Crescendo’s AI-driven knowledge assistant pre-screens content, approving low-risk items automatically and flagging higher-risk materials for manual review by expert AIDEs— Augmented-AI knowledge management.

Conservative Deployment for Maximum Reliability

Crescendo deploys Agentic AI conservatively, emphasizing seamless transitions to human agents whenever the AI encounters uncertainty. This prevents customer frustration and hallucinations, reinforcing trust and reliability in the CX automations.

To safeguard accuracy further, Crescendo provides outcome-based pricing with no cost penalty for handoffs to human agents, backed by stringent quality guarantees.

Balancing Guardrails and Autonomy

Enterprise-level Agentic AI deployments require thoughtfully designed guardrails to maintain brand consistency and operational integrity. Excessive restrictions, however, can reduce AI effectiveness to legacy system levels. Crescendo meticulously refines guardrails across numerous deployments, balancing control and flexibility.

In nuanced situations, Crescendo’s AI leverages general common-sense knowledge from the LLM (e.g., knowing what Bluetooth is) but relies exclusively on an embedded, curated knowledge base for detailed product information. This approach ensures accurate and consistent responses aligned with organizational policies and brand standards, preventing unintended commentary or inaccuracies regarding competitors’ products.

Conclusion

Crescendo’s investment in operational excellence, precise content management, conservative yet ambitious deployment strategies, and sophisticated guardrails places it uniquely at the forefront of Agentic AI innovation. By thoughtfully integrating human judgment, Crescendo ensures unparalleled accuracy and reliability, fundamentally transforming the landscape of customer experience.

In doing so, Crescendo not only redefines what’s possible in CX but also sets new industry standards for AI-driven accuracy and performance.