AI-powered workflow automation identifies and eliminates the manual, repetitive steps in customer service processes — routing, classification, data entry, status updates, and fulfillment triggers — reducing handle time, improving accuracy, and enabling agents to focus on the interactions where human judgment adds value.
Most contact center handle time is consumed by non-value-adding activities: copying data between systems, looking up account information, manually routing tickets, and updating case records. Workflow automation eliminates the manual work so agents spend more time actually helping customers.
Every engagement follows a structured process — from discovery and vendor evaluation to pilot design and scale — adapted to the specific constraints and maturity of your organization.
We analyze your agent desktop recordings and process flows to identify the specific workflow steps consuming the most time — and assess each for automation potential based on rule clarity, system integration feasibility, and error tolerance.
Some workflow steps are fully automatable with RPA; others require AI judgment for classification or routing. We design the hybrid automation architecture that combines rule-based RPA with AI intelligence where judgment is needed.
We evaluate agent desktop automation platforms — NICE RPA, Automation Anywhere, Blue Prism, UiPath — against your agent desktop environment, system landscape, and automation objectives.
Automated workflows fail gracefully when exceptions occur. We design the exception detection, human fallback, and error logging processes that maintain service quality even when automation encounters unexpected scenarios.
These are the evaluation dimensions that consistently separate successful deployments from expensive pilots that never reach production scale.
How many of your agent's manual workflow steps can be automated? Evaluate coverage against your specific systems — legacy CRMs, custom applications, and web-based tools all have different automation accessibility.
Automated data entry and system interactions must be highly accurate — errors in customer records, routing decisions, or fulfillment triggers create serious downstream problems. Validate accuracy on your actual systems.
The primary ROI metric for workflow automation. Evaluate expected handle time reduction against your current handle time composition — what percentage is automatable manual work?
Automation that incorporates AI classification — automatically routing interactions based on intent, sentiment, or customer segment — delivers more value than pure rule-based automation. Evaluate AI decisioning integration.
Desktop automation breaks when application UIs change. Evaluate how the platform handles UI changes — intelligent element recognition vs. brittle coordinate-based automation — and the maintenance burden this creates.
Automation that works well technically but creates a confusing or interrupted agent experience will see low adoption. Evaluate the agent desktop experience with automation enabled across your specific workflows.
"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."
"What set RLM apart was that they didn't have a preferred answer. They evaluated our options honestly and told us what they actually thought."
Start with a no-cost conversation with an RLM AI advisor — vendor neutral, no agenda, just clarity.
Speak to an Advisor