Which Speech AI capability does your contact center need?

What is getting in the way?

A request to repeat something is a symptom, not a diagnosis. The listener might be struggling with background noise, missing audio detail, unfamiliar pronunciation, or a different language. Elsewhere, the conversation may be clear but difficult for the organization to document and learn from.

The following comparison gives you a starting point. More than one problem can be present in the same call, so these capabilities are complementary rather than mutually exclusive.

Speech Enhancement: improve the audio

Removing background noise is useful, but it does not describe every audio problem. A voice can still sound muffled, distant, or thin after the background becomes quieter. Sanas Speech Enhancement addresses the speech signal as well as surrounding distractions.

Sanas's approach includes voice isolation, bandwidth restoration, and correction for acoustic and hardware limitations. This is relevant when agents use different headsets or microphones, or when telephony quality makes speech harder to follow.

Evaluate the voice, not just the silence between words. Does it remain natural? Are words easier to distinguish? If transcription is part of your workflow, assess the effect on your own speech-recognition system too.

Accent Translation: support understanding

When the call is audible and both people speak the same language, pronunciation differences can still create communication friction. Accent Translation refines how speech is heard while preserving the agent's natural voice, emotion, and identity.

It supports the human agent rather than replacing them. Evaluate intelligibility alongside voice preservation: being easier to understand should not require losing warmth, empathy, or a recognizable voice.

Language Translation: cross a language barrier

If the agent and customer need to converse in different languages, clearer audio alone is not enough. Language Translation carries meaning across that boundary. Sanas is designed for two-way, real-time conversations that preserve voice, tone, and intent.

Evaluate the exact language pairs and service situations your team needs. Terminology, conversational timing, emotional expression, and the process for getting human help all matter. A broad language count does not tell you whether a solution fits a specific customer interaction.

Speech Intelligence: make the conversation useful

Some needs begin with what teams do with a conversation. Agents need consistent summaries and next steps. Supervisors need visibility into sentiment, intent, or risk signals. Operations teams need information they can use without relying only on later manual review.

Sanas Speech Intelligence provides call summaries and operational signals, with on-device processing and PII redaction as part of its approach. Review what is processed locally and what structured information is sent onward for the deployment you are considering.

Evaluate the usefulness of the output and who will act on it. A summary needs to capture the important details; a signal needs a clear owner and response process. These capabilities complement communication clarity, but they do not replace operational judgment.

Choose around a real workflow

A multilingual call with poor audio may benefit from both enhancement and translation. A team that communicates clearly may still need help with summaries and supervisor visibility. Start with the most consequential gap, then consider how the capabilities work together.

Bring CX, operations, and IT into the discussion early. A useful evaluation connects the customer experience to agent workflows, deployment requirements, and data handling. The right combination is the one that supports your actual operation, not the longest list of features.

• Identify the communication or workflow problem with representative examples.
• Choose the capability that addresses that problem, and the outcome you will assess.
• Check compatibility, administration, and privacy for that product and deployment.
• Include customer understanding and agent feedback alongside operational measures.