Sales Development Manager

Level AI has launched Latitude, a family of seven purpose-built AI models designed specifically for customer experience tasks. Each model handles a single function: transcription, redaction, summarisation, intent detection, inferred customer satisfaction, quality assurance, and voice of customer analysis. The company claims Latitude matches frontier large language models in accuracy whilst operating at up to 50 times lower cost, with 3.5 times higher throughput and four times lower latency. The models run on Level AI's own infrastructure, meaning customer data never leaves its environment. Level AI analysed 50 million customer conversations between January and April 2026 and found 29% contained sensitive data such as account numbers or medical identifiers. In financial services and insurance, that figure reached 47.1%. VistaPrint reports the system reduced calibration variance from over 20% to 9% across its 1,200 to 1,700 agents in five countries.

Level AI featured as a leader on the CMP Prism for Real-Time Agent Assist: highlighting innovation in CX and agent enablement technology. Jul 14, 2026, 09:00 ET MOUNTAIN VIEW, Calif., July 14, 2026 /PRNewswire/ - Level AI, the full stack, AI-native customer intelligence platform for enterprise contact centers, proudly announces its placement on the latest CMP Prism, for Real-Time Agent Assist. The CMP Prism is an independent, analyst-led evaluation framework that benchmarks customer contact technology solutions against industry standards. CMP Prisms are updated twice annually to reflect the latest advancements, provider performance, and market shifts in customer contact technology. This latest refresh highlights Level AI as a Leading provider, empowering CX and customer contact leaders to optimize their agent enablement strategies and customer engagement outcomes. The CMP Prism for Real-Time Agent Assist evaluated 16 solution providers, including Level AI, and categorized them into five tiers: pioneering, leading, core performing, up & coming, and emerging. These distinctions are grounded in a comprehensive methodology incorporating analyst input, user feedback, and real-world marketplace data across ten investment criteria. "Earning consistent placement across the highest analyst tiers for Customer Analytics, Automated QA, and now Real-Time Agent Assist is powerful validation of our strategic vision to build a single, unified intelligence layer for the entire enterprise customer journey." said Ashish Nagar, CEO of Level AI, "Enterprise CX leaders realize that traditional, keyword-bound point solutions only add desktop complexity instead of resolving it. By delivering an active, context-aware co-pilot driven by our proprietary NLU core, we are helping brands eliminate agent cognitive overload, significantly reduce hold times, and drive absolute process consistency across the entire customer journey." Nicole Kyle, Chief Product Officer of CMP, adds, "CMP Prism benchmarks solutions against industry standards, supported by CMP analysts who contextualize what matters most to your organization. CMP Prism was created to assess solution providers like Level AI to take the guesswork out of tech decisions, replacing vendor spin with objective, research-backed benchmarks." The CMP Prism helps enterprise leaders and tech buyers evaluate solutions and helps providers that are looking to prove their position in the market. CMP also releases Prisms across other strategic technology categories, including customer analytics, chatbots/virtual agents, automated QA/QM, workforce management, and voicebot/conversational IVR. CMP is the customer contact research company. We give leaders clarity, providers credibility, and the industry direction. Independent and trusted, our research powers every corner of the field with actionable insight. Everything the industry needs to move forward, all in one place. Media Contact(s): Jennifer Lewis The Pollack Group 631-521-4960 914-618-0352 Media Contact(s): Lauren Miller Customer Management Practice 914-618-0352 SOURCE Level AI

Q&A with James Manno, Chief Revenue Officer at Level AI. June 30, 2026 James Manno, Chief Revenue Officer at Level AI James Manno is the Chief Revenue Officer at Level AI, a Mountain View, CA-based AI-native platform helping enterprise contact centers turn every customer interaction into operational intelligence. He brings more than nine years of enterprise sales leadership from Qualtrics, where he helped scale revenue from $30M to over $300M and closed more than $500M in net-new Fortune 500 contracts. Manno joins Level AI as the company triples strategic enterprise deals year-over-year and expands into the UK and Latin America. For readers who may be less familiar, can you explain what Level AI does and the challenges it was built to solve? At a high level, Level AI is an AI-native customer experience platform that understands every customer interaction across channels (call, chat, ticket, survey) at scale. We use that intelligence to automate quality assurance, coaching, compliance and every other operational metric you can imagine across the contact center. Level AI was built to solve what has become an acceptable problem that plagues most large enterprises. That being they're making decisions about their customers, agents and performance based on only a fraction of what was actually said. For decades contact centers have reviewed 2-5% of their calls and called it quality assurance. They would send out surveys days after the interaction occurred. By the time anyone did anything about that information, the moment was gone. Level AI changes that by ingesting every call, chat, ticket and survey response to create a single record of what customers are saying and making it actionable in real-time. You spent over nine years at Qualtrics helping scale enterprise revenue from $30M to over $300M. What did that experience teach you about enterprise buying behavior, and how does it apply to what you're seeing at Level AI? The biggest thing I learned at Qualtrics was that enterprises do not buy software, they buy outcomes. The organizations who realized the most value from our platform were the ones who walked into a sales meeting with us knowing exactly what they wanted to do differently and why. The ones who struggled were coming to buy a tool and had no strategy for implementing it. At Level AI I'm seeing that lesson play out again. Enterprises are no longer questioning if AI can help their contact center, they know it can. They are asking which platform can consolidate QA, coaching, compliance and virtual agents into a single system. That is a significantly different conversation than what was happening five years ago and requires a different kind of sales approach. One that's rooted in defining the operational problem you're trying to solve first and the technology to fix it second. Chief Revenue Officer. James Manno. Company. Level AI. Level AI has tripled strategic enterprise deals year-over-year and is now expanding internationally into the UK and Latin America. What is driving that momentum? Product and timing. Our product has finally caught up to the promise of customer experience AI. There are tons of AI companies in our space right now that are years away from having anything I've just described. We are ingesting millions of customer interactions per month for over 100 enterprise customers. Once you start selling into Fortune 500 enterprises your procurement process will chew you up and spit you out if you don't have at-scale, proven results beyond what most can offer. As for timing, the market is finally starting to see what we've been talking about for years. Enterprises have spent the last five plus years slowly evaluating standalone solutions for QA, coaching, virtual agents, etc. and are now at the point where they just want platforms that connect it all. We are winning because we built that platform years before anyone realized they needed it. As for going international, that was always the plan. Enterprise CX teams in the UK and LATAM are dealing with many of the same problems their US counterparts are. They are just as fragmented, and face just as much pressure to modernize. Expanding into those markets was only natural. What does the next generation of enterprise CX look like, and what role does AI play in building it? The next generation of CX is built around having complete data, not sampled data. Every call, chat, ticket and survey feeds into one record that powers QA, coaching, compliance and virtual agents from a single source of truth. Companies that invest in building that kind of infrastructure today are going to have a defensible moat against their competition for the next three to five years. Everyone still running QA on a 2% sample of their data and waiting on survey results to close the loop with customers is going to be stuck continuously reacting to outdated customer insights while their competition is acting on everything their customers are saying. Most AI in the contact center today is still narrowly focused. What separates a point solution from a platform, and why does that distinction matter to enterprise buyers? A point solution solves one problem in isolation from everything else happening in your organization. It might score your calls or power your chatbots but does not tie those two use cases back to anything else in your operation. What ends up happening is your business units go out and buy 5 separate systems that each only see a piece of the customer conversation and never talk to each other. At Level AI we call our customers one, because the same customer interaction that triggers a QA flag also creates the agenda for their coaching session, surfaces a compliance risk and trains your virtual agent for the next interaction. That's what enterprises mean when they say they want a platform. Solutions that connect everything back to a single record of truth about every customer interaction. What is one outdated assumption about the contact center that you believe needs to change? That it's acceptable to measure 2-5 percent of your customer interactions and call it quality assurance. QA teams started doing this decades ago because they were limited by how much review their team could accomplish. With AI, we are no longer bound by that constraint. If you have the ability to review 100% of your interactions, you shift from managing by exception to managing by truth. Every other problem downstream (whether its coaching gaps, compliance risks, or virtual agent training) are that much harder if you're only acting on 2% of your data. The paradigm shift isn't just limited to technology. It's recognizing what you should feel entitled to know about the customers you're serving.