Key takeaways
Real-time agent assist helps agents resolve issues faster and more effectively by providing context-aware guidance during calls.
The reduced handle and hold times improve customer satisfaction.
Agents can stay focused on the conversation instead of searching through information, enabling more natural and personalized interactions.
They also benefit from automations like call summarization and categorization, freeing them from tedious post-call tasks and reducing manual errors.
Introduction
Customer expectations for fast, accurate support have never been higher, but the knowledge agents need to meet those expectations is scattered across CRMs, knowledge bases, and tribal know-how that lives in a veteran rep's head. Real-time agent assist software closes that gap by listening to a conversation as it happens and surfacing the right script, policy, or next-best action before the agent has to go looking for it.
The impact shows up in the data. A study of 5,179 customer support agents by researchers at MIT and Stanford found that generative AI assistance increased productivity by 14% on average, with novice and lower-skilled agents seeing gains as high as 34% (MIT Sloan). In other words, real-time guidance doesn't just make good agents faster, it helps new agents perform like experienced ones from day one.
In this guide, we break down how real-time agent assist works, what to look for when evaluating a platform, and how the leading solutions, including Level AI, Observe.AI, Cresta, and Talkdesk, compare on features, integrations, and pricing.
What is real time agent assist software?
What is real-time agent assist software?
Real-time agent assist software is AI-powered technology that listens to and analyzes customer interactions as they happen, then provides agents with contextual information, recommended actions, knowledge articles, scripts, alerts, or suggested responses during the conversation. It helps agents quickly find the right information without putting customers on hold or switching between multiple systems. By providing guidance in the moment, these tools can help improve agent productivity, consistency, response accuracy, and the overall customer experience.
How real-time agent assist software works: 5 step process
Real-time agent assist software uses AI to analyze customer conversations as they happen and provide agents with relevant information, recommendations, and guidance during the interaction. Below are the steps
Step | What Happens | What the AI Does |
|---|---|---|
1. Capture the conversation | The platform receives the interaction through voice, chat, or messaging channels. | Continuously processes the conversation as it happens. |
2. Transcribe and analyze | Voice conversations are converted into a live transcript. | Analyzes intent, topics, sentiment, and important context. |
3. Understand customer needs | The system considers what the customer is asking and what has already been discussed. | Determines the customer's intent and identifies the appropriate action or response. |
4. Retrieve relevant information | The AI searches connected knowledge sources. | Pulls relevant information from knowledge bases, FAQs, SOPs, product documentation, CRM systems, and other sources. |
5. Provide real-time guidance | Relevant information is surfaced directly to the agent during the interaction. | Provides knowledge articles, suggested responses, next-best actions, troubleshooting steps, compliance alerts, and coaching prompts. |
What to look for in real time agent assist software?
Not all real-time agent assist platforms are built the same. Some focus narrowly on transcription and alerts, while others cover the full loop from live guidance to post-call CRM updates. Here's what to prioritize when evaluating a platform.
Feature | What to Look For |
|---|---|
Real-time transcription with contextual hints and flags | A live transcript paired with dynamic prompts that adapt to the moment, empathy nudges when a customer sounds frustrated, reminders for required disclosures, or compliance flags if an agent offers a discount too early. |
Native workflow integration | Embeds directly into the tools agents already use, such as Salesforce, Five9, Genesys, and Twilio Flex, so there's no separate window or app to manage. |
Intent-based understanding | Understands the underlying meaning of a conversation rather than scanning for keywords, so it still surfaces the right guidance even when a customer phrases their issue in their own words. |
Knowledge base connectivity | Connects to the knowledge sources your team already maintains, including Confluence, SharePoint, Google Docs, and ticketing systems, and surfaces relevant articles automatically. |
Conversational, cited internal chatbot | Lets agents ask questions in natural language and returns answers pulled from the knowledge base and past conversations, complete with source citations. |
Manager visibility and real-time coaching | A live dashboard showing sentiment trends and active conversations, with alerts for events like profanity or a sudden sentiment drop, so supervisors can intervene in real time. |
Automated summaries and CRM write-back | Generates a post-call summary covering the reason for contact, resolution, and follow-up actions, and pushes it directly into the CRM. |
Configurability | Lets you tailor tips, flags, and summary formats to your own workflows and compliance requirements rather than a generic default. |
Want me to keep the short explanatory paragraph above the table too, or should the table stand alone with just a one-line intro sentence?
Why agents need real-time support?
Giving agents the information they need when they need it resolves a few problems that have long plagued customer service:
Agents often juggle several tasks at once, searching for answers, navigating multiple systems, and thinking on their feet, all while maintaining a natural flow of conversation.
Manually searching knowledge base articles while a customer waits can be slow, testing the customer's patience and reducing how many inquiries an agent can handle in a day.
Agents feel unsupported when thrown into complex or unfamiliar situations, which makes escalations and longer resolution times more likely.
Top real time agent assist softwares to evaluate
With this in mind, the rest of this article explains the mechanics of how real-time agent assist works. First, we show features from our own Level AI product, and then compare these to six alternative solutions.
Tool | Key Features | Best For | G2 Rating |
|---|---|---|---|
Level AI | Real-time guidance, intent detection, AgentGPT, auto-QA | Context-aware guidance with strong QA and analytics | 4.6 (220) |
Observe.ai | Auto QA scoring, real-time alerts, coaching insights | QA-first teams adding real-time support | 4.6 (238) |
Dialpad | Assist cards, live transcription, sentiment analysis | All-in-one phone system with built-in AI | 4.4 (708) |
Cresta | Behavioral hints, AutoCompose, outcome-based coaching | Outcome-driven coaching and behavior replication | 4.3 (46) |
Qualtrics XM | Feedback dashboards, sentiment analysis, closed-loop actions | CX teams tracking feedback, not live guidance | 4.3 (751) |
Five9 | Guidance cards, live transcription, call summaries | Native assist within the Five9 CCaaS platform | 4.1 (611) |
Convin | Real-time guidance, auto QA, guided scripts | Real-time assist plus automated QA | 4.7 (549) |
Balto | Compliance checks, dynamic prompts, live QA scoring | Compliance-heavy industries, fast ramp-up | 4.8 (587) |
Talkdesk Copilot | Smart Scripts, knowledge retrieval, agentic AI | Teams standardized on Talkdesk CX Cloud | 4.4 (2,567) |
Genesys Cloud CX | Agent Copilot, omnichannel routing, knowledge suggestions | Enterprise teams on the Genesys platform | 4.4 (1,556) |
1. Level AI : Enterprise real time agent assist software
Level AI’s Real-Time Agent Assist displays for agents relevant knowledge base articles, prompts, and suggested responses during live customer interactions.
Below, we provide examples of how our solution works, but first we want to highlight the importance of detecting intent in conversation when it comes to call center support tools. Many systems today call themselves “AI powered,” but when you peel back the curtain they’re in fact just matching keywords or relying on a rule-based system to trigger responses.
They lack sophistication to truly understand the intent and context behind what’s being said, which gives them only a crude understanding of the conversation.
Here’s an example: a customer complains about a mismatch between what was ordered and invoiced. The system might be trained to recognize such situations by identifying certain words like “invoice,” “mismatch,” “order,” etc.
But people don’t always use the same patterns when they speak. So a customer might express their issue by saying, “There’s something off with these numbers.” Although it might be clear to the agent that a particular item of the bill is under discussion, such a statement might not trigger the keywords the system is trained to recognize.
To catch all such potential situations, administrators typically enter tens (or even hundreds) of keywords for a given intent, but this doesn’t guarantee the system will capture the intent 100% of the time.
Moreover, though a keyword-based system might successfully detect a certain intent, it’s likely to still miss important nuances or underlying issues that tell you the why behind the intent (like a customer’s dissatisfaction in not being given a discount).
This is where Level AI’s natural language understanding (NLU) comes in. Our platform uses NLU and generative AI to detect not only the meanings behind words, but associated sentiments as well, like when someone is unhappy, disappointed, worried, grateful, and more.
While these secure and customizable Generative AI capabilities drive a lot of our post-call analysis features, it also enables our Real-Time Agent Assist to accurately display the right topics at the right time to provide agents with timely support.
Content that adjusts dynamically to the flow of conversation
Real-Time Agent Assist connects directly with your knowledge base and other sources to aggregate all the information and display:
A main feed showing action hints, warnings, and FAQs
Recommend resources retrieved from connected, internal sources like ticketing and knowledge systems
Chat with Your Knowledge Base (search functionality)
As the interaction progresses, the cards shown in both the main feed and resources are updated as new topics under discussion are detected.
All cards feature thumbs up and down icons for up- and downvoting the relevance and helpfulness of the information being shown to agents.
To effectively train the AI, the system offers several categories of negative feedback:
The card would have been helpful but was delayed
The card shows irrelevant results
The information shown on the card is inaccurate, although it may be timely and relevant.
Not only does this help train the AI, but it also keeps your knowledge base up to date, which is important since the completeness of your knowledge base can make or break a real-time agent assist system.
The real-time dashboard also proactively displays scripts and guidance during conversations, as well as a live transcript:
Our Chat with Your Knowledge Base predicts and displays the most relevant search queries during the discussion, automatically surfacing (and summarizing) information from multiple articles to provide at-a-glance answers.
It auto fills the search bar with relevant queries as the conversation progresses:
As you can see on the right side of the screen above, agents will also get conversational answers similar to ChatGPT.
Administrators can configure your front-line chatbot to handover support cases to Real-Time Agent Assist as the need arises.
Using Real-Time Agent Assist, our customers are seeing significant improvements in efficiency and customer satisfaction. For example, Level AI customer ezCater has seen a drop in average handle time of 13%, as well as a decrease in call hold times by as much as 23% during peak support hours. This means that 94% of calls placed by customers during that hour are reduced by 30 seconds, allowing agents to improve efficiency while maintaining the same level of consistent, high-quality service.
Steering agent success with call monitoring
Level AI lets managers guide agents based on real-time call metrics and indicators, such as sentiment analysis, agent performance, deal size, the live call transcript, and more.
Real-Time Manager Assist displays call and customer analytics in a single screen, giving managers an at-a-glance view of ongoing conversations to easily decide where to intervene.
This is in contrast to traditional indicators like whether a call has been going on for too long or if the agent is taking a lot of time for post-call wrap up.
In the past, such criteria didn’t really give managers a clear picture of what was happening on the call, which led agents to sometimes experience interventions by their supervisors as intrusive, since (for example) call duration alone is not an indication that things are faring poorly.
What’s more, supervisors often didn’t have enough context about the conversation (based on their crude metrics) and needed the agent to explain the situation, taking up the agent’s time and effort.
Level AI’s real-time indicators give a much clearer picture of the state of a given call, requiring less effort from all involved to understand a call’s context while generally improving the relationship between managers and agents.
To further explore whether it’s necessary to assist agents, supervisors can click on any of the metrics to display supporting data:
Especially useful are metrics like:
Sentiment score, which shows supervisors how positive or negative a customer currently is on a call (on a scale from 0 to 10, with 1 being extremely negative and 10 extremely positive).
InstaScore, which shows how well an agent is performing according to a predefined rubric.
Coachable insights summing up all the metrics like “High call time” and “Agent recommended a good solution.”
Call duration.
Putting these together, a supervisor might see that during the closing phase of a call, an agent is struggling while customer sentiment drops, and so decides to use the Call Whisper feature to advise the agent on how to handle the situation.
Real-Time Manager Assist also allows supervisors and coaches to easily add agents to the coaching module of Level AI’s post-call QA platform.
Auto-categorizing support conversations
Another way Level AI saves agents time is by automating call dispositioning.
Normally after a conversation, agents must search through a tiered tree of categories to figure out which one is relevant to the conversation they just had.
Then, they manually assign the conversation a category and subcategory. Such exercises are sometimes nearly effortless when the purpose and resolution of the call are clear. But other times, if the agent is unsure how to categorize a call, or they’re weary and stressed, the effort can be time consuming.
Because Level AI can understand what’s being said, it accurately summarizes and categorizes calls based on topics discussed and whether the customer’s issue was resolved, saving agents the time and effort of doing the dispositioning themselves. The outcome of this is also consistently accurate, as the system reduces human error and bias.
Level AI generates such categories based on the intents uncovered during conversations, and for each category associates a number of example terms on which it created the category:
If you create your own, business-specific categories, the system shows example terms for each category, including “near-miss” terms that may or may not be relevant to your intended category. By accepting or rejecting these, you train the AI to better understand and refine its category definitions.
Discover how Level AI empowers you to assist agents
Level AI represents the state of the art in natural language understanding and conversational intelligence, and gives agents the tools to deliver exceptional customer experiences by accurately interpreting and responding to customer needs during every interaction.
Product Ratings
Level AI holds a 4.6 out of 5 rating on G2 based on 220 reviews, with reviewers most often praising its reporting features, ease of use, and the value it brings to coaching and quality assurance workflows (G2).
What are some of the notable customers?
ezCater, QuinStreet, and Globalfaces Direct.
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2. Observe.ai
Observe.ai is a conversation intelligence platform built primarily around post-interaction quality assurance and analytics, with real-time agent assist available as part of the broader platform. It combines speech analytics with automation to score 100% of interactions and surface coaching insights, and its real-time layer adds live prompts and alerts during calls.
Features
Automated quality scoring across 100% of interactions
Real-time alerts and prompts during live calls
Speech and sentiment analysis for call review and coaching
Automated call summaries and notes
Dashboards for tracking agent and team performance trends
Integration with existing CRM and telephony systems
Who It's For
Teams whose primary need is automated QA and coaching at scale, with real-time guidance as a secondary layer rather than the main reason to buy. It suits contact centers already invested in improving quality management who want real-time support added on top.
Product Ratings
Observe.ai holds a 4.6 out of 5 rating on G2 based on 238 reviews. Reviewers consistently highlight ease of use and the depth of its analytics, while some note challenges with sentiment accuracy and setup complexity (G2).
Notable Customers
DoorDash, SoFi, and Affordable Care.
Pricing:
Their sales team can provide you with a price quote for their real-time agent assist feature.
3. Dialpad
Dialpad is a cloud-based business phone and contact center platform with AI-powered features built in, including real-time transcription, live coaching prompts, and automated call summaries. Its agent assist capabilities are part of a broader unified communications platform rather than a standalone product.
Features
Real-time assist cards showing relevant information during a call
Live transcription of calls for reference and review
Sentiment analysis to help managers gauge call direction
Analytics on call volume and agent performance trends
Native integration with Dialpad's phone and messaging platform
AI-generated call summaries and coaching insights
Who It's For
Businesses that want a unified communications and contact center platform with built-in AI features, rather than a separate real-time guidance tool layered on top of existing telephony. It's a reasonable fit for teams that haven't yet invested in a dedicated CCaaS platform.
Product Ratings
Dialpad Support holds a 4.4 out of 5 rating on G2 based on 708 reviews. Reviewers frequently mention ease of use and helpful AI transcription features, with some noting occasional connectivity issues (G2).
Notable Customers
SoFi, Netflix, and Motorola.
Pricing
Dialpad offers a variety of pricing plans starting at $15 per user per month and scaling up to the full enterprise version. A free trial is available.
4. Cresta
Cresta is widely regarded as one of the strongest dedicated players in real-time agent assist, having built the category around live coaching and next-best-action guidance before expanding into quality management and analytics. Its Agent Assist product delivers real-time behavioral hints and compliance reminders during live conversations, informed by outcome data on which agent behaviors actually drive results.
Features
Real-time behavioral hints and compliance reminders during live calls
AI-targeted coaching suggestions based on behavior-to-outcome analysis
Automated quality scoring across 100% of conversations
Live supervisor tools including transcripts and whisper coaching
Generative AI response suggestions (AutoCompose)
Integration with existing CRM and telephony systems
Who It's For
Contact centers where real-time agent assist is the primary requirement and where the team wants coaching tied to measurable outcomes rather than activity metrics. In head-to-head evaluations focused purely on agent assist, Cresta is a strong competitor; it becomes less of a fit when the requirements expand to include a broader platform with post-call analytics and voice-of-customer insights built in.
Product Ratings
Cresta holds a 4.3 out of 5 rating on G2 based on 46 reviews. Reviewers value the real-time coaching and call transcripts, though several note that knowledge assist accuracy and setup time are common friction points (G2).
Notable Customers
Alaska Airlines, Cox Communications, Intuit, United Airlines, and Vivint.
Pricing
According to Cresta’s website, you can request a custom quote from their sales team.
5. Qualtrics XM Platform
Qualtrics XM is an experience management platform built around collecting and acting on customer, employee, and brand feedback. It is not a dedicated real-time agent assist tool. Its contact center capabilities focus more on surfacing customer friction points and feedback trends than on live, in-call guidance for agents.
Features
Real-time dashboards for customer feedback and satisfaction trends
Text and sentiment analysis across feedback channels
Closed-loop action management to route issues to the right team
Survey and feedback collection across multiple channels
Reporting and analytics for CX, product, and brand experience
Integration with CRM and enterprise systems
Who It's For
Organizations whose primary need is enterprise-wide experience management, customer feedback, and voice-of-customer insight, rather than real-time in-call guidance for agents. It's a better fit for CX and research teams than for contact center operations teams specifically evaluating agent assist software.
Product Ratings
Qualtrics Customer Experience holds a 4.3 out of 5 rating on G2 based on 751 reviews, with reviewers praising its flexibility and reporting depth, while some note pricing and setup complexity as drawbacks (G2).
Notable Customers
JetBlue, Shake Shack, and Yamaha.
Pricing
Pricing depends on the pricing a customer purchases, as well the products within a module, such as Frontline Digital or Frontline Care.
6. Five9
Five9 is a cloud contact center platform with a native Agent Assist feature built into its broader CCaaS offering. It provides real-time transcription, guidance cards, and automated call summaries as part of the full Five9 platform, and can also integrate with third-party agent assist tools, including Level AI.
Features
Real-time guidance cards recommending next steps and checklists
Live call transcription
Automatic call summarization to reduce after-call work
Native integration with the broader Five9 CCaaS platform
Workforce and performance analytics
Support for both native and third-party agent assist integrations
Who It's For
Teams already running on the Five9 platform who want agent assist as a built-in feature rather than a separate tool. It suits organizations prioritizing an all-in-one CCaaS platform over a specialized, best-of-breed agent assist solution.
Product Ratings
The Five9 Intelligent Cloud Contact Center Platform holds a 4.1 out of 5 rating on G2 based on 611 reviews. Reviewers highlight ease of use and customer support, with call quality issues and complexity mentioned as common drawbacks (G2).
Notable Customers
Alaska Airlines, Central Bank, and ConnectWise..
Pricing
According to their website, Five9 offers separate pricing depending on what bundle of services and features customers get. Pricing starts at around $175 per seat per month for digital interactions only.
7. Convin
Convin is a conversation intelligence platform built around automated call auditing and quality assurance, with real-time agent guidance and next-best-action prompts added as part of the platform. It focuses heavily on scoring 100% of conversations automatically and turning that data into agent coaching.
Features
Real-time guidance and next-best-action prompts during calls
Automated audit and scoring of 100% of customer conversations
Guided scripts and visual checklists for agents
Proactive alerts during live conversations
Personalized, automated coaching based on call data
Integration with CRM and telephony systems
Who It's For
Teams that want real-time agent assistance combined with automated quality assurance and coaching in one platform, particularly those already prioritizing QA automation as a primary need.
Product Ratings
Convin.ai holds a 4.7 out of 5 rating on G2 based on 549 reviews, with reviewers praising ease of use and the quality of its auditing and reporting features (G2).
Notable Customers
Livpure.
Pricing
Convin pricing depends on features that customers purchase, and prospective customers must speak to a sales rep to get a quote.
8. Balto
Balto is a real-time guidance platform focused specifically on agent assist, delivering dynamic prompts, scripts, and compliance reminders during live conversations. It was one of the earliest companies to build a product specifically around real-time agent guidance, and has since added QA and coaching features on top of that core capability.
Features
Real-time dynamic prompts, scripts, and compliance reminders
Automatic checklist completion as required items are mentioned in a call
Automated call notes and summaries
Real-time QA scoring across 100% of calls
Supervisor tools for identifying coaching opportunities
Integration with major CCaaS platforms including Five9, Genesys, and RingCentral
Who It's For
Contact centers whose primary need is real-time in-call guidance, particularly in compliance-sensitive industries like insurance, collections, and healthcare. It functions more as a specialized real-time guidance tool than a full CX platform, so teams needing deep post-call analytics or voice-of-customer insight alongside agent assist may need to pair it with additional tools.
Product Ratings
Balto holds a 4.8 out of 5 rating on G2 based on 587 reviews, the highest among the tools in this comparison. Reviewers frequently cite ease of use, compliance support, and measurable impact on handle time and conversion rates (G2).
Notable Customers
InteLogix, EmpiRx, Integris Health, and Credit Control.
Pricing
Balto does not publish public pricing tiers, instead using a custom, per-agent-per-month enterprise pricing model that scales based on your seat count and contract length.
9. Talkdesk copilot
Talkdesk Copilot is the real-time agent assist layer within the broader Talkdesk CX Cloud platform. It listens to conversations, understands intent and context, and surfaces answers, guidance, and next-best actions, with newer agentic capabilities that can reason across multiple knowledge sources at once.
Features
Real-time call transcription
Next-best-action recommendations during live conversations
AI-powered knowledge retrieval from connected knowledge bases
Smart Scripts for step-by-step call guidance
Agentic AI assistance for multi-part questions
Automated response generation and post-call summaries
Who It's For
Organizations already using or considering the Talkdesk CX Cloud platform who want agent assist built in natively rather than integrated from a third party. It's a stronger fit for teams standardizing on Talkdesk's full CCaaS stack than for those seeking a best-of-breed, platform-agnostic assist tool.
Product Ratings
Talkdesk holds a 4.4 out of 5 rating on G2 based on 2,567 reviews, one of the highest review volumes among CCaaS vendors. Reviewers praise ease of use and the value of the Copilot integration for reviewing calls and performance metrics (G2).
Notable Customers
Rocky Brands and Quadient.
Pricing
Pricing: Talkdesk does not publicly list a specific price for Copilot; it is offered as an add-on within the Talkdesk platform, with pricing provided through a quote.
Talkdesk directs businesses to request a quote based on their contact center requirements and selected solutions.
10. Genesys Cloud CX
Genesys Cloud CX is an experience orchestration platform for contact centers, with AI-powered agent assist features, including Agent Copilot, built into its broader suite of routing, workforce engagement, and analytics tools. Real-time guidance is one part of a much wider platform rather than a standalone focus.
Features
AI-assisted evaluations and Agent Copilot for live guidance
Omnichannel routing across voice, chat, email, and social
Knowledge base suggestions surfaced during conversations
Speech and text analytics
Workforce engagement and scheduling tools
Open APIs for connecting third-party systems, including Level AI
Who It's For
Large organizations already running or evaluating Genesys as their core contact center platform, who want agent assist as one feature within a much larger CX and workforce management suite rather than a dedicated point solution.
Product Ratings
Genesys Cloud CX holds a 4.4 out of 5 rating on G2 based on 1,556 reviews. Reviewers consistently praise its integration capabilities and feature depth, while noting a steep learning curve for advanced features (G2).
Notable Customers
Accenture and Tata Consultancy Services.
Pricing
Only custom pricing. You can talk to their sales team.
Integrations: Where Agent Assist Lives in the Agent's Workflow
A common thread across customer conversations is that agent assist software isn't a separate tool agents have to open, it's embedded directly into the systems they already use. Rather than a standalone dashboard or browser tab, the assist experience typically loads as an embedded panel inside the agent's CRM or CCaaS platform, most commonly Salesforce, Five9, Genesys, and Twilio Flex.
This matters more than it might seem. Every extra application an agent has to switch between during a live call adds friction, delay, and a chance to lose context on what the customer just said. By embedding directly into the agent's existing workspace, real-time hints, knowledge suggestions, and the live transcript appear right alongside the conversation itself, with no separate login, no second monitor dependency, and no retraining agents on a new interface.
For teams evaluating platforms, this makes integration depth just as important as the AI capabilities themselves. A tool with excellent intent detection is still a poor fit if it can't sit natively inside your CCaaS and CRM stack.
Conclusion: Build better voice experiences with Level AI
Real-time agent assist is no longer a “nice-to-have” for modern contact centers. As customer expectations rise, agents need instant access to accurate information, AI-driven recommendations, and live coaching to deliver faster, more personalized support.
While many platforms offer basic assistance features, Level AI stands out by combining real-time agent guidance, automated QA, semantic intelligence, Voice of Customer insights, and AI-powered workflows in a single platform. Unlike traditional tools that only surface scripts or keywords, Level AI understands customer intent and conversation context to provide truly actionable recommendations during live interactions.
This helps teams reduce AHT, improve CSAT, accelerate agent onboarding, and uncover deeper operational insights across every customer conversation. For businesses looking to scale support quality without increasing agent workload, Level AI delivers a more intelligent and unified approach to real-time agent assist.
Frequently asked questions
How does AI agent assist help reduce average handle time (AHT)?
AI agent assist reduces AHT by automatically surfacing relevant knowledge base articles, scripts, customer history, and next-best actions during live conversations. Agents spend less time searching for information and can resolve issues faster.
Is real-time agent assist useful for remote or hybrid contact center teams?
Yes, real-time agent assist is especially valuable for remote teams because it provides live coaching, guidance, and compliance support without requiring supervisors to monitor every interaction manually.
Can agent assist software improve compliance in regulated industries?
Agent assist platforms help maintain compliance by detecting risky language, providing mandatory disclosures in real time, and guiding agents through approved workflows. This is particularly useful in industries like healthcare, banking, insurance, and telecom.
What features should businesses prioritize in agent assist software?
Key features include real-time transcription, AI-powered recommendations, CRM integrations, knowledge base search, sentiment detection, automated call summaries, live coaching prompts, and quality assurance analytics.
Does agent assist software replace human agents?
No, agent assist software is designed to support human agents, not replace them. It improves agent productivity and decision-making by providing contextual recommendations and reducing manual effort during customer interactions.
How does generative AI improve real-time agent assist?
Generative AI enables agent assist platforms to generate contextual responses, summarize conversations, recommend personalized replies, and adapt guidance dynamically based on customer intent and conversation flow.
What industries benefit the most from real-time agent assist?
Industries with high call volumes and complex customer interactions benefit the most, including contact centers, SaaS support teams, banking, healthcare, insurance, telecom, and e-commerce customer support.
How long does it take to implement agent assist software?
Implementation timelines vary depending on integrations and workflow complexity, but most cloud-based agent assist platforms can be deployed within a few weeks to a few months.
