Balto vs Level AI: Which closed loop fits your contact center?
Both vendors now claim a closed loop. The honest distinction: Balto's starts at the live call. Level AI's starts at QA.
Balto and Level AI both promise to make your team better. They take different paths to get there. Balto, the #1 Rated Agent Assist, QA Automation, and Agentic Insights platform, runs a real-time-first closed loop. Live agent assist fires the cycle, then QA, coaching, and insights close it on shared standards. Level AI, a conversation intelligence and QA automation platform that added native real-time agent assist in February 2026, runs a QA-first closed loop. The platform is built around 100% AI quality scoring, with real-time as a more recent surface on top. Both have a loop. The question is which design center fits your contact center.
What this comparison covers
- check_circleHow Balto's real-time-first closed loop differs from Level AI's QA-first loop
- check_circleSide-by-side feature matrix across 25+ capabilities, filterable by what you care about
- check_circleVerified pricing bands ($75 to $185 per agent per month for Level AI) and what each tier includes
- check_circleHow the comparison plays out for BPO, healthcare, P&C insurance, collections, and home improvement
- check_circleWhere Level AI is honestly the better fit for some contact centers
- check_circleA defensible 60-day plan to switch if you decide to move
Balto vs Level AI at a glance
| Feature | Balto | Level AI |
|---|---|---|
| Founded | 2017 | 2019 |
| HQ | St. Louis, MO | Mountain View, CA |
| Primary design center | Real-time-first. Agent Assist fires in-call, then QA, coaching, and insights close the loop on shared standards. | QA-first conversation intelligence with 100% Auto QA. Real-time added February 2026 as the 'Unified Intelligence Loop'. |
| G2 rating | 4.8 ★ (587 reviews) | 4.7 ★ (200 reviews) |
| Best for | Centers that want real-time-first Agent Assist plus a closed-loop QA, coaching, and insights stack on the same standards. | Centers that want post-call analytics depth and a unified human plus AI agent platform. |
| Pricing model | Per agent per month. Bands shared during evaluation. | Custom. Not officially published. Triangulated at roughly $75 to $185 per agent per month. |
| Typical time-to-value | 4 to 6 weeks | 8 to 12 weeks |
Closed-Loop Scorecard: real-time-first vs QA-first
This scorecard rates Balto and Level AI on the four pillars of the closed loop: real-time guidance, QA, coaching, and insights. What matters is whether each pillar runs on shared standards and whether the loop closes without a manual export.
| Pillar | Balto: Exists | Balto: Native | Balto: Closed-loop | Level AI: Exists | Level AI: Native | Level AI: Closed-loop |
|---|---|---|---|---|---|---|
| Agent Assist | ✓ | ✓ | ✓ | ✓ | ✓ | Partial |
| AI Quality (Auto QA) | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Coaching Workflow | ✓ | ✓ | ✓ | ✓ | Partial | Partial |
| Shared-Standards Insights | ✓ | ✓ | ✓ | ✓ | ✓ | Partial |
What is Balto?
Balto is built around what an agent does on a live call. Agent Assist surfaces required script elements in real time. AI Answers brings knowledge to the screen when an agent or customer raises a topic. AgentGPT handles natural-language operator queries during the conversation. Customer History pulls account context from your CRM at the start of every call, so even a brand-new frontline agent arrives ready.
Those signals don't disappear when the call ends. They become the input the QA pillar scores on shared standards, which auto-feeds the Coaching Inbox, which feeds Insights that update what the AI surfaces on the next call. The closed loop runs across Agent Assist, QA, coaching, and insights without a manual handoff in the middle.
Balto was the first company to bring agent assist to market in 2017. Today the platform powers more than 300 customers and has guided over 600 million interactions in real time across BPO, financial services, insurance, healthcare, and home improvement. Balto holds a 4.8-star G2 rating across 587 reviews, ranks #1 reviewed Agent Assist on G2 and Capterra, and was rated #1 out of 51 evaluated QA solutions in CMP Research's 2026 evaluation.
What is Level AI?
Level AI is a conversation intelligence and QA automation platform founded in 2019 and headquartered in Mountain View, California. Its strongest pillar is 100% AI quality scoring. Automated, configurable scorecards run across every call, and the reporting layer is widely cited as a strength in G2 reviews.
In February 2026, Level AI shipped what it calls a 'Major AI Virtual Agent Expansion' and introduced a 'Unified Intelligence Loop.' That release added native real-time agent assist plus shared-standards framing across human and AI agents. The platform now claims a closed loop, with QA as the design center and real-time built on top.
Level AI carries a 4.7-star G2 rating across 200 reviews and serves a broad enterprise and BPO footprint.
Balto vs Level AI: feature-by-feature comparison
The filterable matrix below covers 25+ features across eight categories. Use the chips above the matrix to filter. Matching rows highlight and the matrix scrolls to that section. Below the matrix, three narrative blocks unpack the highest-stakes dimensions.
| Feature | Balto | Level AI |
|---|---|---|
| Agent Assist | ||
| Live in-call AI Checklist | ✓ Native | ✓ Native (Feb 2026) |
| Real-time compliance prompts | ✓ Native, years-tested | ✓ Native (newer) |
| Agent-facing AI Answers during the call | ✓ Native | ✓ via real-time module |
| Live supervisor alerts on at-risk calls | ✓ Native | Partial |
| AI Quality (Auto QA) | ||
| 100% call AI scoring | ✓ Native | ✓ Native |
| Configurable scorecards | ✓ Native | ✓ Native (rich config) |
| Calibration tools | ✓ Native | ✓ Native |
| QA → Coaching automatic handoff | ✓ Closed-loop, shared standards | Partial. Manual configuration. |
| Coaching | ||
| Coaching session templates | ✓ Native | ✓ Native |
| Agent-level skill tracking | ✓ Native | Partial |
| Coaching items auto-generated from QA failures | ✓ Native | Manual handoff |
| Insights & Analytics | ||
| Operator-facing GenAI (Insights query interface) | ✓ Native | No equivalent |
| Custom dashboards | ✓ Native | ✓ Native (strong) |
| Insights feed back into real-time prompts | ✓ Closed-loop | Partial. Newer, less proven. |
| Pricing & Packaging | ||
| Publicly stated pricing | ✓ Bands shared on request | Officially opaque |
| Per-agent pricing model | ✓ | Custom enterprise only |
| Integrations | ||
| CCaaS integrations (Five9, NICE, Genesys, Talkdesk, Dialpad) | ✓ | ✓ |
| CRM integrations (Salesforce, HubSpot, Zendesk) | ✓ | ✓ |
| Deployment & Time-to-Value | ||
| Typical time-to-go-live | ✓ 4 to 6 weeks | 8 to 12 weeks |
| Self-service playbook editor | ✓ Supervisors update playbooks themselves | Vendor-managed configuration |
| Security & Compliance | ||
| HIPAA BAA support | ✓ Enterprise tier | ✓ Enterprise tier |
| SOC 2 Type II | ✓ | ✓ |
| PHI redaction in transcripts | ✓ Native | Partial |
✓ Native / full capability · Partial or configured where noted.
Feature deep-dive
Three narrative blocks unpack the highest-stakes dimensions.
Agent Assist
Both vendors now have native agent assist. The honest distinction is design center. Balto’s Agent Assist is the trigger of the closed loop. What the frontline agent sees and does in the call becomes the input the rest of the platform scores against. Level AI added real-time in February 2026 as a separate surface on top of its QA-first architecture. For centers that want real-time-first orientation and years of production data behind it, Balto leads. For centers that prioritize post-call analytics with real-time as a supplement, Level AI is competitive.
AI Quality (Auto QA)
Both platforms score 100% of calls automatically, support configurable scorecards, and offer calibration workflows. Level AI’s reporting layer has more depth. Dashboards, trend analytics, and historical drill-down are a recognized strength on its G2 profile. Balto’s QA edge sits in the integration. A failed QA item auto-feeds the Coaching Inbox on shared standards, with no CSV export or supervisor handoff in the middle.
Pricing transparency
Balto publishes pricing per agent per month and shares specific bands with serious evaluators. Level AI publishes no pricing officially. Per-agent bands run roughly $75 to $185 per agent per month, plus $1,500 or more in implementation fees per integration. For procurement teams running side-by-side cost modeling, the transparency gap matters.
Pricing and packaging: Balto vs Level AI
Pricing is one of the few places where the two vendors take genuinely different positions.
Balto
Per agent per month, with bands shared during evaluation. Pricing scales with seat count and contract length. Implementation is typically included on multi-year deals.
Level AI
No public pricing. The vendor runs an enterprise sales motion and quotes are bespoke. Per-agent bands run roughly $75 to $185 per agent per month, plus implementation fees starting at $1,500 per integration. For a 100-seat deployment that works out to roughly $90,000 to $220,000 per year.
| Feature | Balto | Level AI |
|---|---|---|
| Pricing model | Per agent per month | Custom enterprise. Not officially published. |
| Per-agent band | Shared during evaluation | $75 to $185 per agent per month |
| Implementation fees | Typically included on multi-year | $1,500 or more per integration |
| Published transparency | Bands shared on request | Officially opaque |
Deployment, integrations, and time-to-value
Typical time-to-value
Balto: 4 to 6 weeks from kickoff to first live value. Scorecard mapping, playbook design, telephony integration, and supervisor enablement run in parallel. Level AI: 8 to 12 weeks, weighted toward analytics setup and historical data ingestion.
Telephony integrations
Both vendors integrate with the major CCaaS platforms: Five9, NICE CXone, Genesys Cloud CX, Talkdesk, and Dialpad. Balto has built more than 60 integrations across telephony, CRM, and adjacent contact-center systems, with a dedicated integration team on every deployment.
CRM integrations
Both integrate with Salesforce, HubSpot, and Zendesk. Specific integration counts and certifications vary by quarter. Confirm against your current stack before contracting.
Operational independence
Balto's playbook editor is self-service. Supervisors update prompts, scorecards, and compliance triggers without filing a vendor ticket. Level AI's configuration is more vendor-managed, with richer setup options but slower iteration cycles.
Time-to-value: 4 to 6 weeks vs 8 to 12 weeks
Balto kickoff to live. Out-of-box closed loop.
Level AI deployment, including module orchestration.
Balto typically reaches first live value faster. Compounds when leadership is timing AI ROI by the quarter.
The closed-loop difference: real-time-first vs QA-first
Both Balto and Level AI now describe a closed loop. The structural difference is where each loop starts.
Balto's loop originates at the live call. Agent Assist fires, the resulting behavior is QA-scored on the same standards, failed items auto-feed coaching, and insights update what the AI surfaces on the next call. Level AI's loop originates at QA (the platform's strongest pillar) and uses shared standards to manage both human and AI agents in a unified stack. Real-time-first vs QA-first is the honest distinction.
The reason this matters is what happens when AI gets deployed alongside agents. Most AI tools create friction with the people they're supposed to help. Agents see them as a threat. That fear kills adoption, and AI never gets the data it needs. Balto runs the opposite play. One system where AI and frontline agents work together and learn from each other. Agents see AI making them better, not replacing them. And the AI gets smarter because agents are actually using it.
Walk through each pillar in Balto's loop to see how it works in practice.
The 4 pillars in Balto's loop
Agent Assist: the loop trigger
What an agent does on a live call (AI Checklist completion, AI Answers usage, compliance prompt adherence) is the data the QA pillar will score against next. The behavior captured at the moment of the call is the loop's seed. Level AI fires its real-time prompts from a separate playbook layer, decoupled from the QA scoring engine until post-call.
AI QA: scored on shared standards
Balto's QA scores roll into coaching automatically because scorecards are shared with Agent Assist. No CSV export, no manual handoff, no calibration meeting to map two different scoring schemes. Level AI's QA is a recognized strength with deep dashboards. The handoff to coaching is functional but requires more workflow configuration.
Coaching: auto-fed from QA
Skill gaps surface from QA findings. Sessions schedule into agents' calendars. Outcomes feed the insights layer. Balto's Coaching Inbox shows items like 'Talked over the customer' alongside the related call recordings, generated automatically from QA scoring, not authored by supervisors.
Insights: feed real-time on the next call
Insights and the Insights Tab use the same scorecards as the other three pillars, so trends update what the AI surfaces in real time on the next call. The loop closes. Level AI's analytics layer is strong but the integration from insights back into real-time prompts is newer (February 2026) and less production-tested.
See Balto’s Agent Assist in action
Watch a 90-second product walkthrough of how Balto’s live in-call guidance starts the closed loop.
See the productHow Balto vs Level AI compares for your industry
Different industries weight different capabilities. BPO leaders care about real-time agent ramp and per-client scorecards. Healthcare requires HIPAA compliance and clinical script adherence. Insurance needs scripted disclosure prompts during open enrollment. Collections lives or dies by Reg F and mini-Miranda enforcement on every call. Use the tabs below to see the comparison through your industry's lens.
BPO: real-time ramp plus per-client scorecards
- check_circleReal-time AI checklist surfacing answers during new-agent first calls. Balto leads. Level AI's real-time module is newer at BPO scale.
- check_circlePer-client compliance prompts in real time vs flagged in post-call QA dashboards.
- check_circle100% real-time plus 100% AI QA on the same standards vs 100% AI QA only (Level AI's real-time as a separate surface).
- check_circleInsights dashboards segmented per client on shared scorecards (Balto) vs strong post-call reporting depth (Level AI's recognized strength).
- check_circleSelf-service playbook editor (Balto) vs vendor-managed setup (Level AI).
Healthcare: HIPAA plus clinical script adherence
- check_circleHIPAA BAA support: both vendors offer it on enterprise tier.
- check_circleReal-time prompts when agent deviates from clinical script (Balto) vs caught in post-call review (Level AI's real-time is newer).
- check_circleAI Answers surface protocol mid-call (Balto) vs knowledge surfacing via real-time module (Level AI).
- check_circleFull call plus agent action log plus QA scoring on shared standards (Balto) vs full call plus QA scoring with strong post-call audit (Level AI).
- check_circleNative PHI redaction (Balto) vs partial or vendor-configured (Level AI).
P&C Insurance: scripted disclosure prompts at the call
- check_circleLive prompts fire if agent skips a required disclosure (Balto) vs disclosure misses flagged post-call (Level AI).
- check_circleAI Answers surface eligibility rules during quote (Balto) vs knowledge surfacing via Auto QA insights plus real-time module (Level AI).
- check_circleQA plus coaching plus insights on shared standards equals audit-ready (Balto) vs strong audit reporting depth (Level AI's recognized strength).
- check_circleErrors caught before they reach the customer (Balto) vs errors caught post-call (Level AI's real-time growing).
- check_circleSelf-service playbook editor for state variations (Balto) vs vendor-managed configuration (Level AI).
Collections: TCPA plus Reg F real-time compliance
- check_circleMini-Miranda enforcement: real-time prompt fires; agent reads required disclosure before continuing (Balto) vs compliance scored post-call (Level AI's real-time is newer).
- check_circleReg F right-party contact: live prompts walk the agent through validation steps (Balto) vs validation flagged in QA dashboards (Level AI).
- check_circleAbusive-language detection: real-time supervisor alerts on at-risk calls (Balto) vs flagged in post-call review plus real-time module (Level AI).
- check_circleSettlement-offer compliance: agent must hit required script elements; live checklist (Balto) vs post-call QA on settlement scripts (Level AI).
- check_circleCoaching from compliance failures: failed QA auto-schedules coaching (Balto) vs workflow configuration required (Level AI).
Home Improvement: appointment-setting conversion lift
- check_circleLive appointment-setting guidance: AI checklist surfaces required offer elements during call (Balto) vs real-time available, less proven in home improvement (Level AI).
- check_circleObjection handling at the moment: AI Answers surface objection responses live (Balto) vs knowledge surfacing in real-time plus Auto QA insights (Level AI).
- check_circleHigh-value call alerting: live alerts trigger supervisor support (Balto) vs post-call review on high-value calls (Level AI).
- check_circleScript consistency across franchises: self-service playbook editor (Balto) vs vendor-managed configuration (Level AI).
- check_circleConversion-rate visibility: insights dashboards tied to call behavior (Balto) vs strong reporting on conversion analytics (Level AI's strength).
Customer evidence and ratings
Both platforms have strong customer bases. Here’s how reviewers score them and what we heard from teams running real-time-first closed-loop programs.
Balto holds a 4.8-star G2 rating across 587 reviews. Level AI holds a 4.7-star rating across 200 reviews. The star delta is small (0.1) but Balto carries roughly 3x the review volume at a comparable star rating. That’s a larger evidence base behind the rating.
What customers say about Balto on G2
"It is time sufficient & very useful since we are unable to memorize all scenarios[...]. It helps us also for holistic customer experience."
Benedict V.
Sr. Customer Service Assistant
"It gives the user a more effective way to assist the customer's concern through scripts & troubleshooting steps that pop up using audio cues. Because of this, I can efficiently assist the customer without wasting my time looking for resources."
Erica M.
Customer Service Representative
"I love having all the information I need right at my disposal and that it can be updated seamlessly as needed. Balto helps me meet and exceed my monthly quality assurance metrics each month."
Erica C.
Patient Balance Solution Advisor
"I really like Balto's note-taking ability live on the call. [...] Balto helps agents keep track of calls and provides insights into call volume and reasons for calls."
Farzan G.
Desktop Support II / Field Tech
"It keeps me in compliance, with a level of profesionalism, as well it keeps me in a good flow and order for the applications."
Tania S.
License Insurace Agent.
"Balto makes call reviews a breeze. Balto is a great call assistant for our support analysts. It provides reminders of critical call script items and helps guide the analysts through effective call handling. The best benefits start after the call. Analysts are provided customizable call summary information that can be used to fill out tickets, all calls are QA scored, and supervisors are provided AI powered search and analysis features. Balto has been extremely helpful with implementation and recommendations for effective usage."
Verified User
Enterprise, Customer Service & Sales
"Balto is amazing. I like how it captures the conversation. This saves me so much time when logging my call notes. It’s truly amazing and I use it with every call I receive or make. It’s very easy to incorporate words as well. Balto is so easy to use and the features that come with Balto are so helpful. Balto is also very easy to install and integrate into your company’s system."
Diana W.
Small Business, Customer Service
"Very Easy to Use. Balto is the simplest, easy to learn software I’ve used in the industry. I can’t think of a time when I didn’t use it in a call. I use Balto quite frequently throughout my day. Balto is also easy to integrate and implement into whatever software you use. The customer service is top notch and the number of features is fantastic!"
Isaiah
Mid-Market, Sales
"It automatically highlights what you can say to the customer with it's amazing recognition of what customer says. It also now has notes automatically."
Mary Jane M.
"I like that Balto can be tailored to how I specifically talk with customers. I love that it gives me tips when explaining the process to customers."
Lori-Ann H.
"What I love most about Balto is that it keeps me on track when I feel like I don't know where to go next of if I happen to forget what to do next."
Verified User
"I love the Checklist. It's so helpful to see what I've already said/done and the animations help make me feel happy and encourages me on a bad day"
Sha'Quan J.
"Being able to copy and paste the summary notes onto an appointment for a clear understanding by team and all involved of the situation discussed."
Jenna C.
appointment booking
"It's always there to share tips and ideas with how you can improve and allows you to see what you may have missed and needs to be stated."
Wardella B.
"I enjoy the ability to check if I missed any QA questions before an audit so that I can know what parts of the script I commonly overlook"
Denise R.
"The suggested script made it easier for me to ask open ended questions. This helps me converse with the customer and assess their needs."
Angelica B.
"What I like best is that it gives you tips or information while you are speaking. It is very accurate with what you are talking about."
esmeralda u.
CUSTOMER SERVICE ASSOCIATE
"I love the real-time listening. I'm not waiting until after the call to make adjustments, I can make them at the moment I need them."
Verified User
"how balto listens to you on a call, it hears what your saying and then tells you what you have hit and missed keeping you on track."
daniel k.
benefits consultant
"the 1st set of Questions were PERFECT and now you added more thats already and originally part of the Market Place requirement"
Marilyn T.
"Its very helpfull when I'm in need of ways to help get a payment for our company and helps me keep track of the conversation."
Lacy M.
"I like that Balto keeps me on track, helps me to review what I can do better on the next call, and gives real time rebuttals."
Verified User
"That it catches automatically the workflow and allows you to realize what part of the Script you havent said. As well it automatically detects rela..."
Yazmin P.
Account Manager
"That balto really helps out with the quality of service we provide."
Jonathan M.
customer service insurance supervisor
"Most of its features but more on the ability to review data, it help me to quantify the data that I need and help me analyze reports more accuratel..."
Romina T.
Operations Manager
"It's good, especially if it's an outbound calling campaign, because all the objections and what you say can be provided by Balto, and it won't be d..."
Krian S.
Scheduling Coordinator
"Balto can do anything & everything we could want. Which, could be overwhelming, if the content and features weren't explained/trained properly. The..."
Alexis K.
Manager of Guest Care
"My job requires detailed reviews of our phone calls; summaries of what the customer and agent discussed. Instead of trying to recall what was said ..."
Nashon C.
Sales manager
"It has made remote work and training seamless as Balto guides the agent new or experienced through the call, and with dynamic prompts to help with ..."
John Z.
Operations Manager
"Balto helps my team get through their calls and know where to go next without having to disrupt the "human" aspect of the call! They can form rela..."
Beth P.
Data Entry Manager
"Call explorer for myself but the checklist is very easy to utilize and custom with every agent"
Anna R.
Quality Assurance Supervisor and Training Assistant
"Balto has worked continuously with my company to find a happy medium on the kind of summary they are providing after calls. I am more than happy wi..."
Melissa T.
Assistant Account Manager
"I truly appreciate how Balto ensures our customer service is up to par and of top tier quality."
Raphael R.
Stabilization Manager
"Balto is very user friendly. This software is really simple to learn and use. Balto provides increase confidence in its users, let's not forget to ..."
Sarina T.
Assistant Account Manager
"Balto has been helpful for gaining insights, spotting trends, and coaching agents more effectively, which ultimately helps us improve our customer ..."
Aliyah H.
Contact Center Supervisor
"Having a partner like Balto has been great. The features are very helpful to our team and the implementation process was exceptional. Andrew and th..."
Tony J.
operations manager
"It is user friendly and accurate. It has helped me run my team's QA and helped me to be more efficient with feedback."
Tatiana G.
Internal Collections Supervisor
"Balto is fantastic. The company does an amazing job and is continually working to update and innovate."
Sam Wheaton
Contact Center Supervisor
"One of the best tools I’ve used! Whereas before, we took samples of calls, and did as much as we could, but we had hundreds of calls happening daily, and it was pretty impossible to capture all of that. Now people can see what’s actually being said, transcripts can be pulled up, instead of listening to hours of calls. We’ve seen noticeable improvements with close rates"
Alex D.
Call Center Supervisor
"We wanted to find a way to help our team members consistently provide a high level of patient experience every single phone call they had."
Pamela Velasquez
Manager
"This helps newly hired employees feel more comfortable on the phone right out of the gate."
Britni H.
Recovery Specialist Supervisor
"Balto helps guide the conversation and keeps our team consistent and compliant."
Luan D.
IT Leader or Manager
"Balto is Awesome. Balto is very using and populates quick responses and shows us exactly what to say and keeps us compliant."
Anonymous
Enterprise, Customer Service
"It actively listens to your call and suggests phrases to help you out with closing the client through the entire process."
Verified User
"It goes with your call flow. Easy to use, and it tells you how well you are doing along with your team and so much more!"
Lessette L.
"I appreciate how well the Balto app summarizes and organizes conversations. Its user-friendly interface makes it easy to navigate."
John Nero P.
Team Leader
"Balto solves quick objection rebuttals & real-time coaching, eliminating the need for hard copies of sales scripts. The leaderboard stats help me track key points in real-time, increasing my sales."
Mark M.
Sales Group Supervisor
"The software is great. But the implementation process was exceptional! The team we worked with was knowledgable, efficient, & did a fantastic job of getting us up & running with very limited interruption to the team."
Andrew M.
Owner
"It was very easy to write the play book and use the dynamic prompts."
Steven J.
Operations Director
"Everything! The checklist keep my agents on track, the agents love when they get a win and the confetti goes off. I love the dynamic prompts that h..."
Jessica P.
Call Center Director
"I love ho wbalto capture the essence of the conversation & How balto summarize every conversation and provided insights."
John-Nero P.
Associate Director of Admissions
"its AI feature for analytics, and the summarization of each interaction."
Vincent V.
Admissions director
"What I love most about Balto is the real-time coaching feature. It’s amazing how I can get live feedback and guidance during calls, helping me stay..."
Christian E.
ASSOCIATE DIRECTOR OF ADMISSIONS
"Balto's AI to detect what is being said in the call and the ability to prompt the agent on the phone with the right things to say in every scenario..."
Luis M.
Head of Operations
"I really love the real-time speech analytics tool Balto offers. It provides real-time insights into conversations, ensuring we cover everything nec..."
Matthew T.
Director of Portfolio Management
"We infused Balto into our ecosystem, we encourage our team members to utilize the different aspects of the tool, and over the last year, we’ve seen our NPS score take a gradual incline and over the last two months, a very steep incline. There’s a direct correlation with our percent of compliance to our Balto metrics. […] Over the last two months, we’ve consistently been in the 93-95% range and we’re now in a 65-70% range on our NPS score."
Barry Pritchett
VP of Care Logistics
"We had to scale fast and get new agents trained quickly,"
Ken Monroe
VP of Customer Service
"If you wanted to find one specific moment in a call,"
Chip Kennedy
VP of Shared Services
"Before Balto, our supervisors had to listen to each call manually. That’s just not scalable."
James Luxton
VP of Customer Service
"Our blueprint works; but we wanted to help our agents follow it and set them up for success,"
Jeremy Duane
Director of Sales
"Balto has fundamentally changed our onboarding process. We’ve reduced training time from about six months to one month."
Aaron Asher
Owner
"With Balto, agents had the right words at the right moment and our handle time dropped."
Mark Poisson
Director of AI
"If you wanted to find one specific moment in a call,"
Ivonne Ortiz
Director of Training & Quality
"Balto has been a great tool from a coaching perspective and gives our agents real-time rebuttals."
Tony F.
VP of Sales and Business Development
"Balto is a great tool for increasing compliance adherence, conversions, and suggestive call guidance."
Brandon T.
President
"We did a review with one of our agents, and she had been a consistently good agent but not a top sales performer. She was always mid to low in terms of closes. And so we brought Balto in and in that first year, after doing that, her conversion rate literally doubled, which was shocking because nothing else had changed."
Contact Center Technology Leader at Leading Flooring Company
When Level AI might be the better fit for you
Scenario 1: reporting-led programs prioritizing analytics depth
If your QA program is mature, supervisors already know what to coach on, and the constraint is 'we need better dashboards and trend analysis from the calls we've already had,' Level AI's reporting layer is a closer match. Buyer profile: 200 to 1,500 agent center, batch-review QA culture, existing BI investment, supervisor team that prefers retrospective review. What to do next: evaluate Level AI's analytics depth alongside Balto's. If Level AI's reports align better with your BI stack, that's a defensible choice.
Scenario 2: centers building a unified human plus AI agent stack
Level AI's February 2026 'Unified Intelligence Loop' is explicitly designed for this hybrid setup. AI agents inherit human-agent workflows from the same data layer. Balto's loop is built around live human-agent calls. Integrating an AI agent layer would be additive, not native. Buyer profile: contact center actively deploying AI agents in the next 6 to 12 months and wanting one platform to manage both. What to do next: if AI plus human unified management is a near-term priority, Level AI's recent expansion is a real advantage.
If Level AI isn't your fit, see how it stacks up against the wider field of alternatives.
Why contact center leaders pick Balto over Level AI
Real-time intervention beats retrospective review
Catching a compliance miss or sales objection during the call, not three days later, moves the metrics that matter. One Mid-Market Sales and Compliance reviewer on G2: 'Instead of waiting for post-call reviews, I'm able to improve instantly.'
QA-to-coaching automation closes the loop
A failed QA item auto-schedules a coaching session on shared standards. Programs running Balto don't lose continuity between scoring and skill development.
Faster time-to-value: 4 to 6 weeks vs 8 to 12
Real-time-first orientation requires less historical data to load. New rollouts pay back faster, which matters when CFOs time AI ROI by the quarter.
Operational independence
Supervisors update playbooks, scorecards, and compliance triggers without filing a vendor ticket. Speed of iteration compounds.
Proven at scale: 9 years, 300+ customers, 600M interactions
Balto was first to bring agent assist to market in 2017 and has guided over 600 million live interactions since. Collection Systems Inc. cut AHT from 17 minutes to 6. Horizon Services captured $410,000 in added revenue from live alerts. Redirect Health's NPS climbed from 65 to 70% to 93 to 95%.
How to switch from Level AI to Balto: 60-day migration plan
A typical migration from Level AI to Balto runs 60 days end-to-end in three phases. Most centers run the parallel phase deliberately. It lowers risk and gives supervisors a calibration window.
Phase 1: foundations
Export historical scorecard data from Level AI. Map existing scorecards into Balto’s shared-standards model. Connect telephony (Five9, NICE, Genesys) and CRM (Salesforce, HubSpot, Zendesk) integrations. Identify the pilot agent cohort, typically 10 to 20% of the floor, weighted toward representative call mix.
Phase 2: parallel run
Both platforms score the pilot cohort in parallel. Supervisors calibrate Balto outputs against the Level AI baseline week by week. Training rolls out for the real-time plus coaching workflow. By week 5, scorecard variance between the two platforms typically drops below 5%, the sign program leadership has finished calibrating.
Phase 3: cutover and sunset
Expand Balto to the full agent population. Sunset the Level AI contract at the next renewal point. Most centers time the switch to a contract anniversary to avoid double-paying. Establish the monthly review cadence and feedback loop with the Balto CSM.
Centers that skip the parallel-run phase typically regret it. Running both in parallel for a month lets you confirm the closed-loop QA, coaching, and insights flow is producing equivalent or better outputs before committing the entire floor.
Is Balto right for you?
Three questions. We'll tell you honestly, including when Level AI may be the better fit for your contact center.
What would switching save you?
Estimate the operational value of switching from Level AI to Balto. Inputs default to mid-market values. Adjust to your numbers. Outputs show estimated AHT savings, QA coverage value, and the combined annual operational value, not a fabricated cost comparison.
How we calculated this
- Loaded agent labor cost: $40,000 / year (US-typical mid-market)
- Annual productive agent hours: 1,800
- AHT improvement floor: 15% (lower bound of published agent assist benchmarks)
- QA coverage value: $800 per agent per year at full 100% coverage, scaled by (100 minus current %)
- Working days per year: 250
- Balto cost line intentionally hidden. Talk to a Balto rep for a custom quote tied to your specific cost structure.
Balto's own cost stays hidden. Talk to a Balto rep for a custom quote tied to your specific cost structure.
Real-world outcomes across verticals
How to Ditch Call Mining with Real-Time Coaching: Accelerated Receivables Solutions
Accelerated Receivables Solutions had compliance under control, but managers were burning nearly a full week mining call recordings to find coaching moments. Once Balto's Real-Time Coaching alerts let them jump in live the moment a rep went off script, call mining stopped being a job. Managers now spend their hours building new training and QA programs instead.
Read Case Study →Redirect Health Elevates Member Experiences With Balto
Redirect Health's NPS scores were stagnant and reps were nervous AI would replace them. Once Balto's Real-Time Guidance and BaltoGPT post-call review proved to be a co-pilot rather than a threat, compliance climbed from 60–80% to 93–95%, and NPS now consistently lands between 65 and 70.
Read Case Study →From Uncertainty to unmatched NPS: Inside InteLogix's AI-Driven Transformation
InteLogix didn't want to replace its QA processes, it wanted to enhance them. With Balto's AI Workforce, call review dropped from 30+ minutes to under 5, AHT fell 30 seconds, ACW was halved, and one client posted a 24% enrollment lift after Balto pinpointed unclear messaging. QA teams shifted from evaluators to analysts, coaching off truth instead of opinions.
Read Case Study →FAQs
Both Balto and Level AI are AI platforms for contact centers, but they're built around different design centers. Balto is real-time-first. The loop starts when an agent is on a live call, with Agent Assist surfacing the next best step, AI Answers handling knowledge lookups, and live compliance prompts firing in the moment. Level AI is QA-first. The platform is anchored in 100% AI quality scoring of past calls, with real-time agent assist added as a more recent expansion in February 2026. Both vendors now claim a closed loop across guidance, QA, coaching, and insights. The honest distinction is where each loop originates. Balto's starts at the live call. Level AI's starts at the QA layer.
Yes. As of February 2026, Level AI shipped native real-time agent assist as part of its Major AI Virtual Agent Expansion (the launch they describe as a Unified Intelligence Loop). Both Balto and Level AI now have real-time as a capability. The honest distinction is depth and design center. Balto has run real-time as its core orientation for years across more than 300 customers and 600 million interactions. Level AI's real-time is newer and downstream of its QA-first platform architecture.
Level AI does not publish pricing officially. Secondary sources (CheckThat.ai, Ringly's 2026 alternatives roundup) consistently triangulate a band of roughly $75 to $185 per agent per month, plus implementation fees starting at $1,500 per integration. For a 100-seat deployment that's approximately $90,000 to $220,000 per year. Balto's pricing model is per agent per month, with bands shared during evaluation. Both vendors negotiate on contract length and seat volume. Request a custom Balto quote for your specific seat count and contract terms.
As of June 2026, Balto holds a G2 rating of 4.8 stars across 587 reviews. Level AI holds 4.7 stars across 200 reviews. The star delta is small (0.1), but Balto carries roughly 3x the review volume. That's a larger evidence base for the rating. Balto is also ranked #1 reviewed Agent Assist on G2 and Capterra and #1 out of 51 evaluated QA solutions in CMP Research's 2026 evaluation. Verify the current numbers on each vendor's G2 profile before any final selection. Ratings refresh weekly.
Yes. Balto's AI Quality (Auto QA) pillar scores 100% of calls automatically and supports configurable scorecards, calibration, and a dispute workflow. The difference vs Level AI is the integration. Balto's QA findings auto-feed the Coaching Inbox on shared standards, so a failed QA item schedules a coaching session without manual handoff. Level AI has QA and coaching too, but the QA-to-coaching automation requires more workflow configuration.
A typical 60-day migration runs in three phases. Weeks 1 to 2 are foundations: data export from Level AI, scorecard mapping into Balto's shared standards, telephony and CRM integration. Weeks 3 to 6 are a parallel run. Both platforms score the pilot cohort while supervisors calibrate. Weeks 7 to 8 are cutover. Balto rolls out to the full agent population and the Level AI contract sunsets at renewal. Most centers time the cutover to a Level AI contract anniversary to avoid double-paying.
Yes. Running both platforms in parallel during weeks 3 to 6 of a typical migration is recommended, not optional. It lets supervisors compare scorecards side-by-side, calibrate the new Balto setup against known Level AI outputs, and validate before fully cutting over. The parallel phase also lets you confirm the Balto closed loop (QA to coaching to insights) is producing equivalent or better outputs than the existing Level AI workflow. Centers that skip parallel-run typically regret it.
Both Balto and Level AI integrate with the major CCaaS platforms: Five9, NICE CXone, Genesys Cloud CX, Talkdesk, and Dialpad. Both also integrate with the major CRMs: Salesforce, HubSpot, and Zendesk. Balto has built more than 60 integrations across telephony, CRM, and adjacent contact-center systems, with a dedicated integration team on every deployment. Specific integration counts and certifications vary by quarter. Confirm with each vendor against your current telephony and CRM stack before committing.
Yes. Balto supports BAA and standard HIPAA controls (PHI redaction in transcripts, role-based access controls, audit logging) on the enterprise tier. Level AI also supports HIPAA BAA on its enterprise tier. For healthcare contact centers, the more meaningful question is real-time intervention. Balto fires live prompts when a clinical script is missed. Level AI flags the miss in post-call QA. Both are HIPAA-compliant. The workflow difference matters more than the certification.
Yes. Balto supports per-client scorecards, white-label and private-label options, and seat scalability into the thousands of agents. That setup is useful for BPOs running diverse client books. Level AI supports multi-tenant deployments too, but per-client scorecards are configured rather than first-class, and white-label support is more limited. For a deeper look at how the two platforms compare specifically for BPO, see the BPO tab in the industry comparison above.
Both vendors now describe a loop across guidance, QA, coaching, and insights on shared standards. The structural difference is where the loop starts. Balto's loop originates at the live call. Agent Assist fires, the resulting behavior is QA-scored on the same standards, failed items auto-feed coaching, and insights update what the AI surfaces on the next call. Level AI's loop originates at QA (which is the platform's strongest pillar) and uses shared standards to manage both human and AI agents in a unified stack. Real-time-first vs QA-first is the honest distinction.
The most common reasons cited by Balto customers: real-time intervention catches issues during the call, not in a post-call review three days later. That matters for compliance, sales conversion, and CSAT. The QA-to-coaching automation removes manual handoff between supervisors and trainers. Faster time-to-value: 4 to 6 weeks vs 8 to 12 weeks. Self-service playbook editor lets supervisors update prompts without vendor tickets. Balto's track record is 9 years in market, more than 300 customers, and 600 million interactions guided in real time. That said, Level AI is the right choice for some contact centers. See the When Level AI might be the better fit section above.
How we built this comparison
How we built this comparison. Last updated June 11, 2026. Sources: G2 reviews (587 for Balto, 200 for Level AI as of build date); vendor product docs; Level AI's February 2026 'Major AI Virtual Agent Expansion' press release; Balto customer evidence from 39 case studies, 19 testimonials, and 25 G2 reviews; Balto Content Operating System (June 2026 release) for messaging, terminology, and proof points. Refresh cadence: quarterly. If you spot something out of date, let us know.
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