October 2021 Release

Manage human and chatbot interactions across digital and voice channels through a suite of apps.

It's release time! We are excited to share some new features now available within [24]7.ai Engagement Cloud™. With [24]7.ai Engagement Cloud, you leverage an industry-leading conversational AI platform that uniquely blends AI and Human Intelligence (HI) to help you deliver effortless yet stellar experiences across customer interaction channels and devices.

Industry Recognition

What's new in this release:

[24]7.ai Engagement Cloud

Automatic Model Monitoring (AMMO) in [24]7.ai Engagement Cloud:
- Have you wondered how effective your conversational designs are after they’re built and deployed? AMMO is designed to help you stop guessing and start knowing.
- As an extension of the Model Workbench capability that allows building, testing and tuning natural language models, AMMO allows continuous monitoring of intent models and alerts users in real time when conversational designs do not meet desired performance levels.
- With a one-time setup of thresholds, users can easily visualize how different versions of the intent model perform over time, monitor interaction volume, escalations and containment to identify and fix anomalies (e.g., use case: Identify escalation trends over time for billing queries).
- AMMO equips you to proactively analyze, refine, and strengthen conversational designs 10X faster (than typical manual efforts) to continuously improve the customer experience.

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[24]7 Active Share

Offline cards in [24]7 Active Share™:
- Have you had a customer on the phone that isn’t able to complete the transaction because they’re in a hurry or in a place they can’t talk?
- With offline cards, agents can securely send custom visual content as a text message without starting an [24]7 Active Share session (e.g., use case: payment confirmation).
- Offline cards remain active even after the [24]7 Active Share session is terminated allowing customers the flexibility to take action at their convenience (e.g., use case: appointment booking).
- Based on customer actions, agents can complete any necessary follow-up action subsequently (e.g., confirm customer appointment).

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[24]7 Target

Models as a library in [24]7 Target™:
- Do you feel the need to adjust your digital ads after go-live for improved returns? You’re not alone.
- [24]7 Target offers a host of proven machine learning (ML) models that help marketers deliver personalized digital ads across customer-preferred channels and devices to drive improved sales.
- With this new feature, all the curated ML models are now available in an easy-to-access library for advanced users.
- This feature also serves as a framework for data scientists to extend the set of optimization models used in digital campaigns and help drive improved results (e.g., use case: continuous optimization of AI models to suit your unique digital marketing needs).

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Take the Next Step

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