Transform Customer Experience with Generative AI
Generative AI is redefining what's possible in customer experience — enabling dynamic, contextually-aware responses, on-the-fly content personalization, agent assist that generates resolution steps in real time, and knowledge management that writes itself. RLM helps enterprises deploy generative AI in customer experience responsibly and effectively.
What RLM Delivers on Generative AI for CX
The contact center and customer experience market has been transformed by generative AI faster than almost any other enterprise domain. But deploying generative AI in customer-facing contexts requires careful design — hallucinated responses and off-brand outputs in a customer interaction create serious brand and legal risk.
How We Approach Generative AI for CX
Our AI and automation advisory runs from discovery and market evaluation through vendor selection and post-deployment optimization — scoped to the Generative AI for CX decision in front of you.
Generative AI Use Case Scoping
We identify the generative AI use cases in your CX environment that have the highest value and the most manageable risk — agent assist, knowledge article generation, quality scoring, and response drafting — distinguishing these from customer-facing generative AI applications that require more extensive guardrails.
Platform Evaluation
We evaluate generative AI CX platforms — Salesforce Einstein GPT, Google CCAI Insights, Genesys AI, NICE Enlighten AI, and specialized vendors — against your CX stack, use case priorities, and safety requirements.
Guardrails & Safety Design
Customer-facing generative AI must be constrained to accurate, on-brand, compliant responses. We design the retrieval augmentation architecture, output filtering, confidence thresholds, and human review workflows that prevent harmful outputs.
Measurement & Continuous Improvement
Generative AI quality degrades without monitoring. We design the evaluation framework that continuously assesses output quality — accuracy, tone, compliance, brand alignment — and triggers model updates when quality drifts.
Generative AI for CX Selection Criteria
The questions below are the ones that decide whether a Generative AI for CX investment pays back — and the ones vendors are least eager to answer.
Hallucination Rate & Accuracy
Generative AI models produce plausible-sounding incorrect information. Evaluate accuracy on your specific knowledge domain and the guardrails that prevent hallucinated responses from reaching customers or agents.
Brand Voice Consistency
Generated responses must match your brand's tone, vocabulary, and communication standards. Evaluate prompt engineering capabilities and fine-tuning options that enforce brand consistency.
Retrieval-Augmented Generation (RAG) Quality
The best customer-facing generative AI grounds responses in your actual knowledge base rather than relying solely on model training. Evaluate RAG implementation quality and knowledge base integration.
Compliance & Regulatory Controls
In regulated industries, AI-generated responses must adhere to disclosure requirements, prohibited claims, and approved language. Evaluate compliance control capabilities before any customer-facing deployment.
Latency for Real-Time Applications
Agent assist applications require sub-second response latency. Evaluate generation speed under realistic load conditions for your target use cases.
Human Escalation Design
Generative AI must recognize the limits of its knowledge and escalate gracefully. Evaluate confidence scoring, out-of-scope detection, and the quality of handoffs to human agents when the AI can't respond reliably.
"RLM brought structure to a process we didn't know how to start. They asked the right questions, surfaced the right vendors, and kept us from making decisions we would have regretted."
The benchmark comes first. Without a baseline, “savings” is just a number a vendor gave you.
Where This Matters Most
Sector-specific considerations we see repeatedly in ai and automation engagements.
A Sample of the AI & Automation Providers We Evaluate
RLM is vendor neutral. These are among 600+ providers in our evaluation set — inclusion here is not an endorsement, and we are paid by the provider you choose, not by any provider in particular. How that works →
Ready to Move on Generative AI for CX?
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