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Agent assist all channels

Agent Assist software enables contact center agents to resolve customer issues faster and more effectively by providing real-time guidance and automation.

Agent Assist solutions help organizations improve customer satisfaction and reduce operational costs. These platforms use AI to provide agents with real-time support, including knowledge retrieval, automated summarization, and behavioral coaching across all communication channels. They transform contact centers into efficient, customer-centric operations.

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111Verified suppliers
Built for
VP/Head of Customer Experience CIO VP of Contact Center Operations Director of Quality Assurance Knowledge Manager

The challenge

Your organization faces increasing pressure to deliver exceptional customer service while managing costs and agent burnout. Agents struggle to navigate complex systems, leading to inconsistent service and high attrition rates. Customers expect immediate, personalized support, but your agents are overwhelmed by the volume and complexity of interactions. Without the right tools, your contact center risks falling behind, damaging brand reputation and losing revenue.

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30-45% of contact center agents experience annual turnover
17% of agent time is spent on manual case notes
$3T in revenue is lost globally due to poor customer experiences

The solution

Agent assist all channels addresses your unique challenges through modern solutions and key capabilities.

Real-time transcription

Converts spoken words into text with low latency, providing a foundation for real-time guidance and analysis. This allows agents to focus on the conversation rather than manual note-taking.

Contextual knowledge retrieval

Pulls relevant articles and answers from a knowledge base based on the conversation context. This ensures agents have the right information at their fingertips.

Automated call summarization

Generates notes automatically at the end of a call and pushes them to the CRM. This reduces after-call work and ensures data consistency.

Sentiment analysis

Detects customer anger or frustration in real-time, alerting supervisors or prompting the agent with empathy statements. This helps agents tailor their responses to the customer's emotional state.

PII redaction

Automatically scrubs Personally Identifiable Information from transcripts and storage to ensure compliance. This protects sensitive customer data and reduces legal risks.

Generative AI actions

Executes workflows via API integrations, such as processing returns or issuing refunds. This automates tasks and reduces the manual effort required by agents.

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Capabilities Innovation

How to evaluate agent assist all channels

1

Integration ecosystem

Evaluate whether the solution offers native, bi-directional sync with your specific CRM and CCaaS platforms. Avoid solutions that rely on wrapper integrations, as they often fail at scale.

2

Latency and accuracy

Test ASR accuracy on your specific audio data, including diverse accents and jargon. Verify that latency is less than 500ms in a live environment to ensure usability.

3

Total cost of ownership

Look beyond license fees to consider implementation costs, training, API usage fees, and premium support tiers. Understand all potential costs before making a decision.

4

Customizability

Determine if supervisors can update prompts, scripts, and workflows without IT intervention. Agility is key for rapid policy changes and adapting to evolving customer needs.

Questions to ask suppliers

Use these questions during supplier evaluations to ensure you're choosing the right partner for your needs.

Agent assist all channels RFP guide
  • Can you demonstrate your Retrieval-Augmented Generation pipeline using our sample documents, and how do you handle conflicting information in the source material?
  • What is your documented latency for real-time transcription and guidance delivery, and does this change under peak load or when PII redaction is enabled?
  • Describe your specific approach to 'Human-in-the-Loop' for agentic workflows-how does the agent verify and approve AI actions before execution?
  • Do you retain ownership of the data derived from our interactions to train your foundation models, and can we opt-out while retaining full functionality?