Give Every Agent Expert Guidance in the Moment
Real-time agent assist AI listens to customer interactions and surfaces relevant knowledge, suggested responses, compliance reminders, and next best actions in real time — giving every agent the support of a seasoned expert without requiring them to search for help manually.
What RLM Delivers on Real-Time Agent Assist
The best agents are effective because they know where to look, what to say, and when to escalate. Real-time agent assist brings that expertise to every agent, on every call, from day one — dramatically compressing the time-to-proficiency curve and improving consistency across the contact center.
How We Approach Real-Time Agent Assist
A structured path through the Real-Time Agent Assist decision — current-state discovery, shortlist and benchmark, commercial negotiation, then support until it is actually working.
Assist Use Case Scoping
We identify the specific assist moments that have the highest value in your interaction types — knowledge retrieval, objection handling, compliance reminders, next best action, escalation guidance — and prioritize the development of each.
Platform Evaluation
We evaluate real-time assist platforms — Cresta, Level AI, Cogito, Genesys Agent Assist, Google CCAI Agent Assist — against your contact center platform, interaction types, and assist objectives.
Knowledge Integration & RAG Design
Real-time assist is only as good as the knowledge it can surface. We design the knowledge base integration and retrieval architecture that gives the assist system access to accurate, current product and policy information.
Agent Adoption & UX Design
Assist tools that add cognitive load or interrupt natural conversation flow don't get used. We design the agent desktop integration and UX that makes assist feel like a natural extension of the agent's workflow.
Real-Time Agent Assist Selection Criteria
Before committing to any Real-Time Agent Assist platform, these are the points worth forcing a straight answer on.
Suggestion Accuracy
Irrelevant or incorrect suggestions are worse than no suggestions — they interrupt agent focus and erode trust. Validate suggestion accuracy on your specific interaction types before deployment.
Latency of Real-Time Suggestions
Real-time suggestions must appear within the natural conversation flow — typically within 1-2 seconds of the triggering utterance. Evaluate processing latency under realistic concurrent load.
Integration with Agent Desktop
Assist suggestions must surface in the agent's existing workspace — not require them to switch to a separate application. Evaluate integration with your specific agent desktop platform.
Knowledge Base Integration
The quality of suggestions depends on the quality and currency of the underlying knowledge. Evaluate how the platform integrates with your knowledge management system and handles knowledge updates.
Compliance Trigger Accuracy
Compliance reminders must fire reliably when required disclosures or prohibited topics are detected — not trigger false positives that create alert fatigue. Validate compliance trigger accuracy on representative interactions.
Manager Analytics
Real-time assist generates rich data about interaction patterns, knowledge gaps, and agent performance. Evaluate manager-facing analytics capabilities that leverage this data for coaching and process improvement.
"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 →
Thinking About Real-Time Agent Assist?
Start with a no-cost conversation with an RLM AI advisor — vendor neutral, no agenda, just clarity.
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