Top 18 Real-Time Agent Assistance Platforms in 2024

Learn about the 18 best real-time agent assistance platforms of 2024, perfect for improving customer service and support workflows.

Aug 5, 2024

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Top 18 Real-Time Agent Assistance Platforms in 2024

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In AI customer support, effectively addressing customer queries and issues is crucial for improving customer experiences and boosting sales. Imagine a customer contacts your support team for help and expects a quick resolution, but your agents need help to provide a satisfactory answer due to the issue's complexity. How can you overcome these challenges and offer real-time agent assistance to enhance customer experience and increase sales without incurring extra costs?

ChatBees offers an AI customer support solution that can significantly streamline your support processes. It provides real-time agent assistance, ensuring that your agents can promptly and accurately address customer queries, ultimately enhancing customer service KPIs.

What Is Real-Time Agent Assistance?

Real-time agent assist is a revolutionary feature of conversation intelligence that leverages AI and machine learning to provide sales and support reps with real-time guidance during customer interactions. This technology analyzes the:

Context

Sentiment

Intent behind the customer's words

Through natural language processing (NLP) and machine learning.

Understanding the conversation in real-time suggests the best:

Responses

Actions

Solutions

Based on customer history, mood, and the product. This real-time guidance is similar to having an intelligent assistant beside you, offering relevant information, suggestions, and tips precisely when needed.

Capabilities of Real-Time Agent Assistance

Real-time agent assist operates as a whispering coach for sales and support teams, enhancing their performance during live chats or calls with customers. Here's how it works:

Listening and Learning

The AI agent listens to every:

Word in the conversation

Comprehending the context

Sentiment

Intent behind the customer's words

Analyzing and Suggesting

The system quickly determines the best responses and actions based on the conversation, customer history, and other data points, such as product details and overcoming objections.

Supporting on the Spot

Instead of waiting until after the call, the agent receives these suggestions as the customer interaction unfolds, providing information needed to navigate tricky customer questions effectively.

Improving Over Time

With machine learning, AI tools enhance their suggestions by learning from past conversations, making them more accurate and helpful as they progress.

A Scenario of Real-Time Agent Assistance in Action

Consider a scenario where a customer calls about a complex subscription renewal issue. Here's how the conversation might differ without and with real-time agent assistance:

Without real-time agent assist

The customer explains their issue.

The agent manually searches for information, potentially putting the customer on hold.

The agent might need to include crucial details or offer the best solution, which could lead to a more extended call or the need for a follow-up.

With real-time agent assist

The customer begins explaining their issue.

The real-time agent assist system analyzes the speech and context as they speak.

The system identifies keywords related to the issue, offering real-time prompts to the agent.

The system suggests solutions, customer history, and previous interactions without manual searches.

The agent effectively addresses the customer's issue and upsells based on the AI's recommendation.

Ticket Resolution

Automated Ticketing System

Customer Service Knowledge Base

Slack for Customer Support

Ticket Triage

AI For IT Support

Ticket Handling Best Practices

Automated Email Response Customer Service

AI Ticketing System

8 Major Benefits of Real-Time Agent Assistance

1. Effectiveness

Real-time agent assistance helps improve the effectiveness of customer service engagements by providing:

Guidance on the right points to achieve the desired resolution

The best nudges to improve key outcome

Customers most likely to achieve the best outcomes

Accounts are unlikely to reach a resolution

By knowing which actions drive the best outcomes, agents can become more effective in various industries, such as debt collections or healthcare revenue cycle management.

2. Reduced Ramp Time

Real-time agent assistance can significantly reduce the training time for new hires, enabling them to start taking calls faster. Providing constant and engaging reinforcement of training topics more interactively reduces training expenditures by over 30 percent.

3. Increased Productivity

Agent assistance tools help agents focus on outcome-focused activities rather than:

Training session

Recalibration

Refreshers

By guiding agents through calls and offering in-call mentorship, these tools improve agent productivity by over 20 percent.

4. Improved Compliance Adherence

Real-time agent assistance can help agents adhere to compliance guidelines more effectively by providing reminders and coaching during every call. This solution allows for adding and configuring new compliance guidelines quickly and easily, thus enhancing compliance adherence by 10-15 percent.

5. Better Customer Experience

Using an agent assistance tool can significantly enhance the customer experience by guiding agents through conversations to ensure they are:

Focused

Empathetic

Contextually aware

6. Increased Agent Focus

Agent assistants help reduce agents' distractions during calls, allowing them to focus on building better connections and conversations. By supporting agents through each call's technical flow and guidelines, these tools improve agent focus and interaction quality.

7. Just-in-Time Coaching

Real-time agent assistance provides clear next actions exactly when agents need them, keeping them engaged and focused during conversations. This form of coaching occurs in real time, ensuring agents have the support they need during every call.

8. Higher Job Satisfaction

Real-time agent assistance can enhance job satisfaction by offering engaging gamification, leaderboards, and in-the-moment interaction. Better performers are less likely to leave their roles, and with practice and excellent coaching, agents can improve their performance significantly.

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How Does Real-Time Agent Assist Work?

Agent assist listens to conversations and automatically identifies a customer’s sentiment, history, and reasons for their call. It then uses this live information, data on the customer’s past interactions and insights from other interactions to make recommendations specific to each call.

These recommendations are helpful because they help agents focus on listening to the customer rather than digging through menus. An AI-powered agent assist feature can recognize when it’s appropriate to deliver in-call reminders to the agent, like when they’re heading off-script or out of compliance, when they should show more empathy for the customer, or when to offer a discount to an unhappy customer.

Integration of AI with Customer Service Platforms

Behind all this is a dual-layering of AI technology: natural language processing and machine learning. Natural language processing (NLP) is a branch of AI that focuses on making sense of human speech and written text. With the help of statistical methods and machine learning algorithms, NLP can understand the context and meaning of what people say or write.

Monitoring Conversations and Providing Relevant Suggestions

While simple speech-to-text software can transcribe what we say into written words, NLP goes further by understanding complex phrases and terminology and extracting more abstract qualities like sentiment from a message. The way we speak and write is wildly complex, but our brains are good at understanding the meaning and intent behind someone’s words – even if they’re spelled wrong or delivered in a roundabout way.

Understanding NLP Software: Mimicking Human Language Processing

NLP software mimics how our brains process language to understand meaning and context. NLP uses various statistical methods, processes, and language detection tasks. These include:

Speech-to-text: This converts human speech into text.

Tagging and categorizing: This uses machine learning to sort words into categories like nouns and verbs.

NLP can also recognize names and entities, such as people’s or place names. Once the text or audio has been processed, NLP can use natural language understanding and deep learning models to identify emotions and positive or negative sentiments.

Use of Natural Language Processing (NLP) and Machine Learning

Machine learning is a characteristic of an AI engine that helps algorithms improve over time, much like human brains do. If you think back to how you learned to read, write or do math, you’ll recall that you probably started out getting a lot of things wrong.

But with the correct:

Teaching

Direction

Repetition

You slowly improved over time. That’s how machine learning works. The main difference is that AI networks aren’t learning with any inherent sense of consciousness or awareness.

Understanding Machine Learning: Learning Without Awareness

While they can and do become incredibly complex, machine learning processes must be made aware of the why behind their learning. A great example of this is a machine learning AI that is getting to grips with levels of Super Mario games.

The AI here can learn that doing X or Y results in Mario losing a life, so it’ll do something different next time until it completes the entire level. But it doesn’t know that it’s playing a computer game or why. That’s machine learning in a nutshell.

Top 18 Real-Time Agent Assistance Platforms in 2024

1. ChatBees

ChatBees focuses on optimizing Real-Time Agent Guidance (RAG) for internal operations, such as customer and employee support. The software boasts accurate responses and easy workflow integration through a low-code, no-code approach.

ChatBees' agentic framework enhances response quality, enabling operations teams to handle higher query volumes without needing DevOps for deployment and maintenance.

2. Observe AI

A standout feature of Observe AI is speech analytics, which analyzes customers:

Conversations' tone

Sentiment

Context

To provide agents with effective call-handling feedback. The software now offers real-time guidance, making it a valuable tool for enhancing agent performance during live interactions.

3. Abstrakt

With rapid real-time capabilities (0.2 seconds), Abstrakt ensures agents receive instant guidance during conversations. The software is easily configurable, doesn’t require extensive coding or training, and integrates seamlessly into existing tech stacks.

4. Cresta

A significant player in the industry, Cresta focuses on coaching agents across calls and chats. The software prioritizes AI-driven coaching and offers features like a whisper and barge for real-time support during conversations.

5. Uniphore

Uniphore combines automation and conversational AI to provide real-time agent assistance, seamlessly transitioning between virtual and live agents. The software also offers dashboard and analytics features to enhance operational efficiency.

6. Level AI

Known for its speech analytics capabilities, Level AI later added real-time support features to aid agents during interactions. The platform integrates ChatGPT as an add-on option, leveraging APIs to enhance agent performance.

7. Genesys

Genesys is a prominent contact center software provider that offers intelligent automation features to automate tasks during customer interactions. It excels in optimizing agent workflows and enhancing operational efficiency.

8. Five9

It focuses on system overhauls, offering technology similar to Genesys and specializing in virtual-to-live agent handoffs. The software also analyzes customer sentiment and emotions, leading the pack in sentiment analysis development.

9. Talkdesk

Provides agents with tools and resources to improve customer interactions. The platform offers comprehensive agent assist software bundled with omnichannel capabilities for enhanced customer service.

10. Vsynergize

Boasts over two decades of domain expertise in providing omnichannel customer support. The software combines human expertise with advanced AI capabilities to revolutionize customer support services and enhance customer satisfaction.

11. Tidio

Leverages AI-powered capabilities to revolutionize customer interactions. Features like the Reply Assistant automate responses to frequently asked questions, while Smart Views help identify support opportunities and optimize workflows based on user behavior.

12. Help Scout

Employs AI-powered agent-assist solutions to enhance customer support operations seamlessly. Features like SupportAgent.ai, powered by OpenAI's advanced GPT -4 model, accelerate response times and improve the quality of customer interactions.

13. Netomi

A market leader in AI for customer support, Netomi offers cutting-edge technology to streamline customer interactions and elevate support efficiency. The Generative AI-powered virtual agent, Netomi Agent Assist, seamlessly integrates into existing workflows.

14. Balto

Empowers contact center agents with real-time guidance for delivering perfect conversations on every call. With industry-leading AI for behavior change, Balto boosts agent performance, leading to happier customers and increased revenue.

15. Cognigy

Equips service agents with real-time intelligence through Agent Copilot to manage customer queries efficiently. Cognigy enables agents to deliver consistent and seamless customer experiences with features like contextual handover and emotional intelligence support.

16. Kore.ai

Enhances customer support and agent experiences through real-time assistance powered by generative AI and Large Language Models (LLMs). Features like Next Best Action recommendations and real-time coaching enhance agent productivity and customer satisfaction.

17. Level AI

Revolutionizes contact center performance with its cutting-edge Agent Assist platform. The Real-time Agent Assist boasts 2X accuracy in understanding customer intent and offers features like Autonomous Learning and coaching to enhance agent performance.

18. Haptik

Empowers agents with AI-powered suggestions, guided workflows, and real-time training for effective query resolution. The platform ensures consistent, personalized support, reducing resolution time while enhancing customer satisfaction.

Ticketing System Workflow

Help Desk Process

Hubspot Ticketing System

AI Customer Service Agent

Digital Customer Service Tools

Ticket Management System

AI Customer Service Software

Service Desk Automation

Slack Ticketing System

Customer Service Automation Software

Help Desk Analysis

Help Desk Automation

Automated Customer Support

2 Main Use Cases of Real-Time Agent Assistance

1. How real-time agent assistance helps sales teams

Cold calling is challenging. Even when you find a potential customer, following up and delivering a convincing pitch is tough. AI is significantly simplifying this process for sales teams.

Real-time agent assistance utilizes current data and customer interactions, integrating with CRM systems to create precise profiles for each prospect. This helps the sales team tailor pitches that genuinely resonate with customers’ needs and wants, including their budget and personal preferences.

How Agent Assist Keeps Sales Calls on Track with Real-Time Feedback

Even with careful planning, sales calls can veer off course. Here, the agent assists steps in by providing real-time feedback and suggested responses to sales reps. It offers tips on adjusting their approach, what questions to ask, how to respond, and how to close the deal.

In summary, AI for sales helps reps:

Customize their pitches

Understand how the prospect feels

Answer questions more effectively

Close more deals

2. How real-time agent assistance supports contact center agents

Effective problem-solving and consistent service are essential in customer support. Sticking to rigid scripts can miss the mark for individual customer needs.

Real-time agent assistance gives agents the tools to tailor responses to each customer’s unique situation while following company guidelines. This technology provides real-time guidance, possible responses, and prompts to help agents handle complex interactions, ensuring consistency and accuracy.

Integrating AI Agent Assist with CRM Systems for Enhanced Customer Insights

Many AI agent-assist solutions also integrate with CRM systems, giving agents access to customers' past interactions and information before they answer the call. This helps agents better meet customer expectations and needs.

Real-time Agent Assist for Improved Coaching

Real-time assistance is also great for coaching and empowering new agents. It can monitor new agents’ performance, providing real-time prompts and suggested responses during interactions. This speeds up training, helps new agents gain confidence, and improves performance with guidance.

6 Challenges and Limitations of Real-Time Agent Assistance

1. Limited Scope

One key challenge when utilizing real-time agent assist tools is their limited scope. These tools excel at handling routine tasks but may struggle with more complex customer issues outside their designated tasks.

Real-time assistance software is usually tailored to handle a specific set of tasks. If faced with a situation outside these predefined tasks, the tools need to be equipped to address them adequately. To mitigate this challenge, companies can pair AI assistance with human intervention to handle intricate issues requiring human judgment.

2. Lacking Human Touch

Despite advancements in AI technology, real-time agent assist tools still need to catch up in replicating the human touch essential in customer service. Understanding the emotional aspect of customer interactions poses a significant challenge for these tools.

They may find it difficult to reply with empathy or fully grasp a customer's emotions during a conversation. To address this, companies can leverage AI tools to handle routine tasks while reserving complex interactions for human agents to maintain the human touch and emotional intelligence needed for exceptional customer service.

3. Over-Reliant Agents

Real-time agent assist tools can unintentionally lead agents to over-reliance on immediate answers, hindering their learning and development. If agents heavily depend on these tools, they may not cultivate the problem-solving skills required to handle complex situations independently.

This over-reliance may result in stagnant skill growth among agents. To combat this challenge, organizations should encourage their agents to leverage AI tools as aids rather than replacements, keeping a balance in their use to foster continuous learning and skill development.

4. Data Privacy Concerns

Processing customer interactions by real-time agent assist tools raises data privacy concerns that must be addressed proactively. While analyzing customer conversations by AI tools might comply with data regulations, some customers may feel uneasy knowing that AI analyzes their interactions.

Companies should prioritize data privacy and security, clearly communicating how AI tools enhance customer service without compromising privacy. Transparency and proactive measures to safeguard customer data can help alleviate these concerns and build customer trust.

5. Integration Challenges

Real-time agent assist tools, often designed for user-friendliness, can pose challenges when integrating with existing systems and workflows. Customization may be necessary to align these tools with specific contact center workflows and software, demanding significant time and resources.

Incorrect configuration during integration can disrupt established processes and hinder optimization. To address this challenge, thorough planning and collaboration between the IT and customer service teams are vital to ensure seamless integration and minimize disruptions to operations.

6. Technical Issues

Real-time agent assist tools operating in live customer interactions are vulnerable to unexpected technical issues impacting service quality and customer satisfaction. Technical glitches such as:

failure to provide prompts

lagging in real-time interactions

complete tool malfunctions during service calls

It can have immediate and detrimental effects.

To mitigate this risk, companies should invest in robust technical support, conduct regular maintenance and testing, and have contingency plans to address any unforeseen technical issues promptly.

Maximizing AI in Customer Support: Overcoming Challenges for Optimal Benefits

While real-time agent assistance offers significant benefits, addressing the potential downsides and obstacles is crucial for maximizing the value of AI in customer support. By acknowledging these challenges and implementing proactive strategies, businesses can leverage AI tools effectively to enhance customer experiences and drive operational efficiency.

Use ChatBees’ AI Customer Support Software to 10x Customer Support Operations

ChatBees is a revolutionary AI customer support software that optimizes RAG for internal customer and employee support operations. This innovative tool focuses on providing the most accurate responses and seamlessly integrating them into existing workflows.

Key Advantages of ChatBees

The agentic framework automatically selects the best strategy to enhance response quality across various use cases.

Improved predictability and accuracy, enabling operations teams to handle a higher volume of queries efficiently.

No DevOps support is required for deployment and maintenance, making it a hassle-free solution for customer support needs.

Benefits of Using ChatBees for AI Customer Support

Boosts response accuracy and reduces the burden on your teams.

Empowers operations teams to handle a higher volume of queries without compromising quality.

Integrates seamlessly into existing workflows for a smooth transition with minimal disruption.

Enhances customer support operations without the need for complex coding or maintenance.

Transform Your Customer Support with ChatBees

With ChatBees, you can expect a tenfold improvement in your customer support operations without needing a credit card. Simply sign in with Google and embark on your journey towards more innovative, efficient customer support with ChatBees. This opportunity will enhance your customer support operations and elevate your business.

Ready to revolutionize your customer support operations? Try out ChatBees’ AI customer support today and witness a remarkable transformation in how you handle queries and support requests.