Real-time agent assist for contact centers is an AI-powered technology that supports human agents during live interactions by providing instant answers, coaching, and automation.
Teams can work faster, stay consistent, and deliver better customer experiences with real-time support across industries like:
- Healthcare
- Finance
- Retail
- Food and beverage
- IT
With tools like automated QA, real-time suggestions, and AI-driven knowledge search, companies can lower costs, reduce burnout, and improve both service quality and efficiency.
Real-time agent assist for contact centers is a set of AI and automation tools that support agents during live interactions across channels, helping to provide context, speed up resolutions and automate post-call work. According to Hubspot, 90% of people expect immediate assistance when reaching out to a company and may easily take their business elsewhere if you don’t respond fast enough. But without the right tools, even the best support teams struggle to deliver fast, effective service.
Industry leaders like AmeriHealth Caritas, Carrefour, PepsiCo, and many more businesses leverage real-time agent assist features to empower their support teams, helping them provide service that’s:
- Faster
- More efficient
- More personalized
The result? Happier teams, satisfied customers, and smoother operations all around.
In this guide, we’ll explore:
- What real-time agent assist is
- How agent assist technology works
- The key 6 benefits of real-time agent assist tools
- Ways these solutions can transform the way you work based on your industry
What is real-time agent assist for contact centers?
Real-time agent assist for contact centers is a technology that helps human customer service agents navigate and resolve live interactions across channels faster and more effectively.
It usually comes as a third-party system that integrates into your company’s backend processes. During calls with customers, your team can consult right then and there with their real-time agent assist for contact centers or have it running on the side while interacting with customers.
In essence, real-time agent assist solutions work by:
- Listening to conversations via speech-to-text for calls or text stream for chats
- Using natural language processing (NLP) and sentiment analysis to understand the customer’s intent, emotions, and context to help agents
- Immediately surfacing relevant knowledge base articles or FAQs, recommended responses or scripts, compliance reminders or upsell cues, and sentiment alerts
Finally, the human agent can review and use the suggestions in real time.
Due to its real-time, 24/7 assistance, this technology is gaining a lot of attention. The global real-time AI agent assist market is expected to grow from USD 4.4 billion in 2024 to around USD 124.6 billion by 2034 (Market.Us, 2024). So, if you’re wondering whether it’s worth it, the time to integrate these features is now—because your competitors are probably already investing in helping their teams work faster and be more productive.
What are the main real-time agent assist features?
Real-time agent assist offers a unique opportunity to give your team their own personal digital colleague that can help them whenever they have a question mid-call or chat with a customer, as well as when they need to find information about the company, policies, or other internal resources.
From quality assurance to live chat and agent coaching, these are just a few features you can expect after integrating this technology into your processes. Let’s go over some of the key ones.
- Automated quality assurance: Top voice AI for agent assist in real time automatically monitors and scores customer interactions across calls, chats, emails, etc., for quality, compliance, and performance, without needing human reviewers. For example, the system can flag and let the agent know if they didn’t verify the customer’s identity or missed a required disclosure. It can also provide real-time QA scorecards to let your agents and supervisors know the quality of each interaction.
- Automated coaching: AI-powered agent assist analyzes agent performance in real time and, after calls or chats, provides personalized feedback and tips to improve skills. For example, it can suggest something like, “You spoke too fast during the last minute. Try slowing down to improve clarity.”
- Live chat: An AI-powered platform enables real-time text communication between customers and agents, with AI assisting both sides. For instance, while chatting, the AI can suggest instant replies or retrieve relevant FAQs for the agent.
- AI suggestions: The agent assist system listens to the conversation and provides real-time recommendations such as next best actions, replies, or resources. Say a customer asks about a refund; the AI instantly surfaces the company’s refund policy.
- Transcription: The speech-to-text technology behind most agent assist tools can transcribe live calls into readable text in real time, enabling search, analysis, and compliance tracking. In this case, supervisors can see a live transcript to assist agents during escalated calls.
- Call summarization: After a call, AI automatically creates a short summary of what was discussed, including key points, actions, and outcomes. An example could be a simple note after the call: “Customer reported a billing error. The agent escalated to finance. Follow-up scheduled for Friday.” It can also automatically transfer this information to a CRM system and attach it to a client’s record.
- Knowledge management: An AI-powered knowledge base delivers the most relevant answer or resource instantly when triggered by keywords or intent. For example, Capacity, an AI-powered internal and external support automation solution, offers Answer Engine® for internal teams, where they can search for information by giving it prompts and receiving only relevant details instead of links to documentation or FAQs.
Live customer sentiment: AI continuously analyzes tone, language, and emotion during interactions to gauge the customer’s mood—such as positive, neutral, negative, or frustrated. For example, if frustration increases, the system alerts the agent or supervisor in real time.
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Why use real-time agent assist?
Call and contact centers use real-time agent assist to process interactions and surface relevant suggestions, knowledge articles, or next-best actions within the same conversational moment, without the agent needing to stop and search.
Real-time agent assist solutions have great benefits for your business, team, and customers:
- Cheaper cost per call: Companies that have already implemented AI in their call center services are reporting measurable gains, with some seeing a 50% reduction in cost per call (McKinsey, 2025).
- Shorter handle times. Agents don’t pause to look things up because the right information arrives as the customer is still explaining the issue. For example, Klarna, a payment solution, integrates AI at multiple business layers. Results? It managed to reduce issue resolution time from 11 mins to 2 mins.
- Higher first-contact resolution. With complete, contextually relevant guidance available in the moment, agents are less likely to give incomplete answers or need to escalate.
- Faster ramp for new agents. Real-time assist effectively closes the experience gap, giving newer team members the same in-the-moment support that an experienced agent has built up over time.
- Consistent compliance and quality. Because the system monitors every conversation continuously, it can surface compliance prompts or flag sensitive topics the instant they arise — not after a QA review catches them a week later.
Most AI tools in support environments operate on a request-response model: an agent submits a query, the system processes it, and a response comes back. This is how async summarization tools, post-call analytics, and batch QA scoring work. That model is well-suited to tasks that don’t need to happen in the moment, like generating a call summary after the conversation ends or flagging compliance issues in a nightly audit batch.
Real-time agent assist is architecturally different. Rather than waiting for a complete input and returning a single output, it uses streaming inference — the model receives and processes tokens (individual words or word fragments) continuously as the conversation unfolds. Using speech recognition technology, it understands what customers and agents are saying and updates its understanding with every new word.
This continuous processing is paired with low-latency inference pipelines — the infrastructure layer that ensures model outputs are returned fast enough to be useful within a human conversational turn, typically targeting under 300–500 milliseconds from input to surfaced suggestion.
How does agent assist technology work?
Real-time agent assist is made possible by different AI-powered technologies and the synergy between them. Let’s go over the main technologies that make it possible to get information instantly, summarize conversations, and move data between systems.
AI understanding for listening and analyzing in real time
At the core of agent assist is AI that “listens to” and understands live customer interactions to:
- Identify intent, such as “I want to cancel my order”
- Detect emotion, such as “The customer sounds angry”
- Track context, including previous interactions, authentication details, and purchase information
Without it, suggestions would fall flat, as the system would have to rely on pre-developed scripts and prompts instead of “thinking” for itself.
Generative AI for creating real-time support and insights
Generative AI takes understanding a step further by creating content and guidance instantly, such as:
- Suggesting replies or summaries written in a human tone
- Retrieving real-time knowledge, like “Here’s the warranty info for Model X”
- Offering coaching, like “Try empathizing before offering a discount”
Generative AI models trained on your business data can mimic top-performing agent behavior, producing personalized, compliant, and empathetic responses.
Integrations for connecting data across systems
To experience the full power of agent assist, it must integrate with other systems you already use in your operations.
Agent assist can (and should) integrate with:
- CRM systems
- Knowledge bases and helpdesks
- Ticketing tools
- Telephony or CCaaS platforms
For example, if it summarizes a call, it can automatically transfer that information to your CRM platform. Or if an agent needs information about specific policies, agent assist can pull it directly from your omnichannel helpdesk.
Automation and workflow intelligence for reducing manual work
An advanced AI-powered agent assist system can automate repetitive tasks such as:
- Capturing call notes using speech-to-text
- Tagging conversations
- Summarizing outcomes
- Updating CRM fields
It can also use AI-driven routing to match customers with the best agent based on intent, skill, or sentiment. This way, agents can focus on relationship-building rather than administrative work.
Feedback loop and learning for continuous improvement
AI-powered technologies enable real-time agent assist systems not only to help, but also to learn from each interaction so they can provide better assistance over time.
Every interaction trains the AI further:
- Successful responses strengthen future suggestions
- Negative sentiment triggers retraining or new coaching rules
- Supervisors can fine-tune guidance templates
The system continuously learns, becoming smarter, faster, and more context-aware—without you having to manually upload information every time there’s an update or change.
What are the 6 benefits of real-time agent assist tools?
The benefits of agent assist range from improved agent efficiency to a better customer experience, as your team has all the necessary tools to provide top-notch service. Let’s go over some of the main benefits for your team and customers.
1. Consistent support
AI-powered real-time agent assist works like a brain behind the scenes. So, whether a customer contacts your team multiple times or speaks with different people, they still get the same experience and information because agents can access everything from a unified knowledge source. Every customer receives the same high-quality, accurate, and compliant response, no matter who they speak to.
To ensure consistent support:
- AI provides real-time answer suggestions and compliance reminders during calls and chats
- Knowledge bases and generative AI ensure agents always use approved, up-to-date information
- Automated QA continuously checks for adherence to standards and provides real-time QA scorecards
2. Effective team training
It can take anywhere from three to six weeks to teach a new hire the ropes of your business processes (Procedure Flow, 2021). Agents improve much faster with targeted, continuous coaching rather than relying solely on their initial training, learning videos, or documentation.
AI helps agents train faster and more efficiently by:
- Automated coaching to highlight performance trends and skill gaps
- Offering guidance while interacting with customers
- Providing real training examples, automatically tagged for coaching moments
3. Faster resolutions
When you give your employees the right tools, they solve issues more quickly, reducing handle time and customer frustration.
One study showed that developers using generative AI completed programming tasks 55.8% faster, demonstrating AI’s strong potential to boost agent productivity (arXiv, 2023).
AI for customer support also reduces resolution time by:
- Giving suggestions and delivering instant information
- Making real-time transcription and summarization to keep agents focused on the conversation
- Integrating with CRM and ticketing systems to eliminate app-switching
4. Lower support costs
Many AI-powered automation platforms offer AI assistants to help lower support costs. For example, Poly.AI, an agentic AI platform, delivers conversational AI, voice automation, and internal support features designed to cut costs by optimizing your team’s work and customer experience. It’s a great option for small businesses that want to automate mundane and repetitive service tasks.
However, regardless of the platform, top voice AI for real-time agent assist can help cut costs in several ways:
- Operational efficiency improves, allowing teams to handle more interactions with fewer resources
- You need fewer staff members since AI features help your current team manage more inquiries
- Onboarding becomes faster, and new hires make fewer mistakes
As a result, you can expect fewer escalations, reduced overhead, and better ROI per agent.
5. Lower agent attrition
According to the Bureau of Labor Statistics, call center quit rates are almost five times higher than in almost any other occupation. At the same time, 87% of call center workers report high or very high stress levels, and as many as 77% say they experience high or very high personal stress (Professor Virginia Doellgast and Dr. Sean O’Brady, 2020).
However, with the right tools to help your team do their jobs more efficiently, agents stay longer because they feel supported, capable, and less stressed.
For example:
- Real-time assistance reduces the anxiety of handling tough interactions
- Agents receive positive feedback loops through performance analytics and coaching
- Less repetitive work and better tools improve job satisfaction
And for your business, that means lower turnover, lower recruiting costs, and stronger institutional knowledge.
6. Better brand experiences
A common situation in support centers: a customer calls to ask about their order because they want to cancel it and get a refund. Your agent takes the case but needs time to find information about this particular order, confirm whether it can be canceled at that stage of shipping, and process the refund.
The customer grows increasingly frustrated while waiting and may even receive incorrect information. On the other hand, when your team has real-time assistance, they can access the right information within seconds. As a result, customers walk away feeling heard, helped, and valued every time they interact with your business.
What is an example of agent assist? 5 real-world industry cases
If you have a customer support team in your company, you can definitely benefit from using real-time agent assist technology. Teams in healthcare, finance, retail, and many other industries enjoy easier, faster, and more accurate assistance with the right tools. Let’s explore how different industries benefit from agent assist technology.
1. Healthcare
Real-time agent assist software in healthcare can help agents:
- Collect patient symptoms during live calls
- Find the best times for visits
- Update patient records without any manual work
For example, many healthcare providers struggle with insurance verification. Usually, a business receives many insurance verification calls. The problem is that they’re highly variable and prone to error — different payers have different rules, coverage varies by plan, and agents need to navigate nuanced eligibility questions in real time. A real-time assist system can surface the right payer-specific guidance the moment the conversation turns to benefits or coverage, reducing both handle time and the risk of agents giving inaccurate information that leads to claim denials downstream.
A great example of a successful agent assist implementation is Humana, a health insurer. Together with Google Cloud, the company developed an AI agent assist solution to help over 20,000 support agents handle customer inquiries more accurately and quickly. It’s a challenge as the company receives 80 million calls annually. But with the new agent assist tools, Humana expects to generate more than $100 million of savings over a few years.
Real-time agent assist supports agents by surfacing context, guiding next best actions, and automating routine steps, even when you’re dealing with highly regulated industries like healthcare.
2. Financial services
Financial services like banking and mortgages require systems capable of ensuring top-notch security and compliance.
When implemented properly, real-time agent assist in financial services can help agents find customer information faster, check account details, and authenticate customers more quickly without repetitive steps.
For example, Paramount Residential Mortgage Group, Inc. (PRMG), a leading lender in the mortgage industry, integrated Capacity’s agent assist features into their internal employee support. Like many large corporations, PRMG struggled with excessive time spent on manual and repetitive tasks and scattered information.
Capacity’s digital assistant now provides loan and guideline information to employees without human involvement. As a result, about 90% of those questions are now answered by AI.
Complex products, high transaction volumes, and a constant need for speed and accuracy are no obstacle to an advanced AI agent assist platform.
3. Retail
Retail is a great example of how agent assist helps agents handle hundreds of customer inquiries in a fast-paced environment without stress.
Customer support teams in retail can rely on AI-powered assistants to help customers get answers and solve problems on the spot. However, AI technology for internal processes can do much more than just suggest tips or coach agents.
It can also:
- Check live inventory levels across stores or warehouses mid-conversation
- Instantly surface sizing, compatibility, or product specification details to answer shoppers’ questions
- Apply discount codes or loyalty points to an order without leaving the call
- Initiate an exchange or replacement order directly from the support interface
- Pull up a customer’s full purchase history to handle warranty or receipt requests on the spot
- Identify cross-sell or upsell opportunities based on what the customer just bought
- Flag items the customer mentioned as out of stock and suggest available alternatives
Some of the biggest retailers successfully implement the technology to empower their staff. For example, Nike uses two AI-powered tools — AgentAutosys, which automatically detects and resolves job failures, and Genius Results, a self-service assistant trained on over one million past incidents. As a result, with the help of AI, Nike’s customer support can handle thousands of repetitive IT tasks and support queries.
4. Food and beverage
The food and beverage industry can successfully implement and utilize agent assist features to help their teams manage partner and customer-facing tasks. A great example of a successful agent assist implementation is PepsiCo, a food, beverage, and snack corporation behind Pepsi, Lay’s, Gatorade, and many more iconic brands you probably have in your pantry.
As an international multibillion-dollar corporation, PepsiCo faced a challenge: valuable information was stored in data silos around the world, and employees struggled to find it.
To help optimize their projects, PepsiCo turned to Capacity and deployed the Answer Engine®, a platform that connects their corporate knowledge into one accessible search engine for teams.
Rather than spending hours searching for specific files or information or guessing about the effectiveness of advertising campaigns, employees can simply ask for what they need. The Answer Engine® searches through millions of pages of content across both first- and third-party connections to find answers in seconds.
As a result, PepsiCo can now access millions of consumer insights and save more than 438 hours each month.
5. IT support
Real-time agent assist acts as an AI co-pilot for IT support teams, providing instant access to relevant knowledge base articles, troubleshooting steps, and suggested responses during live interactions. When your team doesn’t have to spend their entire day answering simple FAQs, they can focus on resolving issues more accurately.
Beyond efficiency, agent assist boosts agent confidence and job satisfaction, leading to lower burnout and attrition.
At IBM, for example, an internal agent assist system for IT teams pulls knowledge from multiple sources, such as app documentation, ticket systems, and training videos, and uses AI to deliver fast, relevant answers for IT teams.
Another great feature for IT teams is secure screen sharing and screen recording. Sometimes, an agent just can’t solve a problem during a call and needs to access a customer’s or colleague’s screen. What most people worry about in these cases is their privacy and security. That’s why Capacity created a feature called Cobrowse. It allows IT staff to safely access a screen and solve problems remotely—without risking privacy or security violations.
Support your agents in real time with AI-powered agent assist
It’s clear that real-time agent assist can transform how your team finds information, helps customers, and experiences their time with your business.
These benefits are just the beginning.
The technology also provides:
- Consistent support
- Effective team training
- Faster resolutions
- Lower support costs
- Lower agent attrition
- Better brand experiences
If you want these and many more benefits for your team, you won’t want to miss Capacity and its real-time agent assist tools—created for large teams that need an extra hand managing their day-to-day tasks. If better utilization of your support team, improved customer experiences, and smoother information exchange between systems sound good, request a demo!
Capacity Can Do?
FAQs
Intelligent real-time assist is an advanced version of agent assist that uses AI and machine learning to understand intent, emotion, and context as a conversation unfolds.
It can:
– Coach agents live
– Surface relevant knowledge
– Generate personalized responses
Agent assist is typically integrated into a contact center platform or CRM system, and it should work seamlessly once set up.
Agents simply work as usual while the AI quietly listens in and provides:
– Live prompts and knowledge recommendations
– Sentiment alerts and coaching tips
– Automated call summaries and CRM updates
Your real-time agent assist KPIs will depend on your unique case. However, most companies notice:
– Reduced average handle time (AHT)
– Increased first contact resolution (FCR)
– Improved customer satisfaction scores (CSAT/NPS)
– Lower agent attrition rates
It shortens handle time by eliminating search and guesswork. AI delivers the right answer instantly instead of agents searching multiple systems. Automation also handles repetitive tasks like note-taking and tagging.
By putting the right information in front of agents as the customer is still speaking, live guidance reduces handle times, improves first-contact resolution, and shortens ramp time for new agents. It also enables consistent compliance monitoring across every interaction, rather than catching issues after the fact in QA review.
The three most common hurdles are system integration, data quality, and agent adoption. Real-time assist needs to connect cleanly with your existing CRM and knowledge base — fragmented systems produce unreliable guidance. That knowledge base also needs to be current and well-structured before go-live, which is often more work than teams anticipate.
Finally, agents need to experience the tool as something that takes pressure off them, not monitors them — how you frame the rollout makes a significant difference to how quickly the team gets on board.
