Prompt

Can you recommend agent assist software for suggesting next best actions during high-volume support calls?

Artificial Intelligence / AI Customer Service1 observationLast seen Jul 21, 2026

Latest observation

Jul 21, 2026OpenAI APIWeb search: off

Yes — for high-volume support calls, you’ll want agent assist software that can do more than basic transcription. The key capability you’re asking for is real-time next-best-action guidance: suggesting the right script, knowledge article, troubleshooting step, escalation path, or offer based on the conversation context.

Top agent assist options to consider

1) Genesys Cloud CX

  • Strong for contact centers with high call volume
  • Real-time transcription and guidance
  • Can suggest knowledge articles and next steps during the call
  • Good if you already use Genesys for routing/CCaaS

2) NICE Enlighten / CXone

  • Very strong in large enterprise contact centers
  • AI-powered agent assist, summaries, and guidance
  • Good at compliance-heavy environments
  • Often used for next-best-action and live guidance

3) Google Cloud Contact Center AI (CCAI)

  • Excellent real-time speech understanding and intent detection
  • Can surface relevant articles and prompts dynamically
  • Good if you want to build a customized assist flow
  • Works well for organizations already on Google Cloud

4) Amazon Connect + Amazon Q / Contact Lens

  • Cost-effective and scalable
  • Real-time transcription, analytics, and agent guidance options
  • Good for teams looking for flexibility and AWS-native integration
  • Strong if your support stack is already on AWS

5) Microsoft Dynamics 365 Customer Service + Copilot

  • Good for organizations already using Microsoft stack
  • Can recommend actions, summaries, and knowledge content
  • Best when CRM context matters a lot in the call

6) Salesforce Service Cloud + Einstein Copilot

  • Useful for support teams embedded in Salesforce
  • Can surface case context, knowledge, and suggested responses/actions
  • Best for Salesforce-centric environments

7) Cresta

  • Purpose-built for real-time agent assist and coaching
  • Strong next-best-action recommendations
  • Often chosen for sales/support call centers that want live behavioral guidance
  • Good for improving handle time and adherence to best practices

8) Observe.AI

  • Strong AI for live agent assist, QA, and call insights
  • Can suggest responses and actions in real time
  • Good for coaching-heavy teams and call centers focused on quality

What to look for specifically

For your use case, prioritize tools with:

  • Real-time transcription
  • Intent detection
  • Context-aware next-best-action prompts
  • Knowledge base integration
  • CRM/ticketing integration
  • Live compliance guardrails
  • Low latency so prompts appear while the call is still happening
  • Multilingual support if needed
  • Post-call summaries and auto-dispositioning

Best choices by scenario

If you want a mature enterprise contact-center suite:

  • NICE CXone
  • Genesys Cloud CX

If you want best-in-class AI guidance:

  • Cresta
  • Observe.AI

If you want cloud-native/build-your-own flexibility:

  • Google CCAI
  • Amazon Connect

If your support team lives in CRM:

  • Salesforce Einstein Copilot
  • Microsoft Copilot

My practical shortlist

If I were narrowing this down for high-volume support calls, I’d start with:

  1. NICE CXone
  2. Genesys Cloud CX
  3. Cresta
  4. Observe.AI
  5. Google CCAI

These are the most relevant if your main goal is next-best-action guidance during live calls rather than just call summarization.

If you want, I can also give you:

  • a comparison table by features and price tier
  • recommendations based on your current CRM/contact center
  • or a vendor shortlist for SMB vs enterprise

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

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Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

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