Remove Communication Barriers in Every Customer Interaction
AI-powered accent neutralization reduces friction in voice interactions between agents and customers — improving first-call resolution, reducing repeat contacts, and enabling enterprises to leverage global talent pools without compromising customer experience quality.
What RLM Delivers on Accent Reduction
Accent misunderstandings cost enterprises in handle time, repeat calls, and customer satisfaction. AI accent reduction technology processes agent audio in real time, neutralizing heavy accents without altering the agent's natural voice — removing the communication barrier without the personal cost of accent training.
How We Approach Accent Reduction
A structured path through the Accent Reduction decision — current-state discovery, shortlist and benchmark, commercial negotiation, then support until it is actually working.
Use Case & Population Assessment
We assess the volume of interactions where accent barriers measurably impact resolution rates or customer satisfaction — using your existing QA data, CSAT scores, and handle time analysis to identify where accent reduction delivers ROI.
Platform Evaluation
We evaluate accent reduction platforms — Sanas, Krisp, and others — against your contact center platform, agent hardware, and voice quality requirements.
Integration with Agent Desktop & Telephony
Accent reduction runs as a real-time audio layer between the agent and the customer. We design the integration with your telephony platform and agent desktop to ensure reliable, low-latency operation.
Quality Assurance & Agent Feedback
Agent trust in the technology is critical for adoption. We design the QA process and feedback mechanism that validates audio quality and incorporates agent preferences into configuration.
Accent Reduction Selection Criteria
Before committing to any Accent Reduction platform, these are the points worth forcing a straight answer on.
Latency Impact on Audio Quality
Real-time audio processing introduces latency. Evaluate the impact on conversation naturalness — round-trip audio latency must remain below human perception thresholds to avoid creating new communication barriers.
Voice Quality Preservation
Accent reduction must not degrade audio quality, introduce artifacts, or create an unnatural voice effect that customers find off-putting. Evaluate on a representative sample of your agent voices.
Agent Opt-In vs. Mandatory Deployment
Some enterprises deploy accent reduction as optional tools that agents control; others deploy it at the platform level. Evaluate the deployment model and its implications for agent trust and adoption.
Integration Complexity
Integration with your telephony platform (Genesys, NICE, Avaya, Amazon Connect) determines deployment complexity and reliability. Evaluate integration maturity against your specific platform.
Privacy & Data Handling
Real-time audio processing requires careful data handling. Evaluate where audio is processed (on-device vs. cloud), retention policies, and compliance implications for your industry.
ROI Measurement Framework
Accent reduction ROI is measured through handle time reduction, first-call resolution improvement, and CSAT impact. Establish baseline measurements before deployment to validate post-deployment value.
"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."
Every engagement is measured against the baseline we establish at the start — not against a vendor’s projection.
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 Accent Reduction?
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