Maven AGI: The $250M Enterprise AI Co-pilot for Customer Experience

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Hi 👋, this is the Today in AI Newsletter: The weekly newsletter bringing you one step closer to building your own startup.

We analyze a cool, industry-shaping AI startup every week, with a full breakdown of what they do, how they make money, how much they’ve raised, and the opportunity ahead. 

Let’s get to the good stuff in this email: 

• 📈 This startup is reimagining the customer journey with AI agents

• 🚀 They hit $7M ARR in February 2025, just 5 months from launch

• 💰 They’ve already raised $78 million from Dell, Cisco, M13 and others.

So what’s the startup and who are the founders behind it? Here’s the story of Maven AGI 📈

Maven AGI is an AI-native customer experience platform that lets enterprises scale support through autonomous agents - without losing the personal touch.

These aren’t your average chatbots. Maven’s agents are deeply integrated, action-capable assistants that can ingest enterprise data, understand full customer context, and resolve tickets entirely on their own. 🤖

Whether it’s answering a billing question, kicking off a campaign, or troubleshooting a compliance issue, Maven’s agents are built to do, not just talk. 🧱

The outcome? Massive support cost savings, faster resolutions, and a new standard of customer experience. 💨

How it works is Maven plugs directly into the heart of an enterprise’s tech stack: Salesforce, Zendesk, Gainsight, Amplitude, Snowflake, you name it. 

From there, it builds context-rich AI agents trained on structured and unstructured data, allowing them to make sense of fragmented systems, internal knowledge bases, and even telemetry logs. 💎

These agents aren’t static workflows. They reason across datasets, trigger API calls, write summaries, launch tasks, and escalate only when necessary. ⚙️

For example: instead of replying “check your settings,” a Maven agent can access the user’s config, detect the issue, and resolve it autonomously.

Support teams can deploy agents with minimal effort. No code required. 🧑‍💻

Maven’s long-term ambition is to build Business AGI - a world where every team has an intelligent agent that works across systems, understands goals, and delivers outcomes. 💼

Imagine an AI CFO that generates reports, monitors spending, and answers investor questions. Or an AI GTM lead that launches campaigns and syncs with CRM and analytics. 

That’s where Maven is headed. And they’re just getting started. 🚀

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Backstory 👀

Jonathan Corbin grew up in small-town Pennsylvania, raised by a single mom who worked multiple jobs to support the family. 🧑‍🤝‍🧑

After business school, he spent a decade in customer-facing roles, eventually heading global Customer Success at HubSpot.

There, he saw how expensive and inefficient enterprise support could be. Despite the tech, people were still repeating themselves. He knew there had to be a better way. 💡

Sami Shalabi, the technical visionary, was born in Egypt and moved to the U.S. for school. 🇪🇬

He earned a PhD in Computer Science from Georgia Tech and eventually became a Distinguished Engineer at Google. 🖥️

His work touched everything from Google News to mobile search, and he holds over 55 patents. He’d seen how personalization at Google scale could serve billions - but also how hard it was to replicate that context in enterprise software.

Eugene Mann was the son of Chinese immigrants who ran a family restaurant in New Jersey. 🇨🇳

He studied statistics at Harvard and later worked in product & data science at Uber and then Stripe. At Stripe, he helped lead applied ML - dealing with high-stakes issues like fraud, compliance, and transaction failures. 

He was also part of the first wave of users to get access to GPT-4 in stealth, and instantly saw its potential to transform the way enterprise users interact with software. 🥷

Three different upbringings. One shared belief: the way enterprises serve customers is fundamentally broken - and LLMs could finally fix it.

Early Beginnings 🐣

The idea for Maven wasn’t born in a boardroom. It was built over years of friendship.

Sami and Eugene first crossed paths during early LLM meetups in San Francisco. Jonathan and Eugene met through mutual friends in the GTM world. 

Eventually, all three ended up at the same dinners, the same whiteboard sessions, the same rec basketball games. And every time they met, the same theme kept coming up: customer support was broken. 😔

Ticket deflection tools didn’t work. Chatbots were dumb. Human agents were overwhelmed. Enterprises were bleeding money. 🩸

But it wasn’t until late 2022 that everything clicked.

OpenAI had just released early previews of GPT-4. Eugene was one of the first to try it. 🤩

“This is different,” he said. The hallucinations were down. The reasoning capabilities were real.

For the first time, there was a path to replacing fragmented support tooling with agents that could reason across systems, respond with full context, and take action. 🤖

He called Jonathan: “It’s time.”

The three met for a weekend sprint - no slides, just product thinking. The energy was instant. They aligned on a wedge: enterprise support - a space they each knew intimately. 

By week’s end, they had a name, a deck, and $8 million in seed funding at a $40M post-money valuation led by Lux Capital and E14. 💰

Stats 📊

Since then, Maven AGI has been on a tear.

💸 They hit $7M in ARR by February 2025 just 5 months from launch, and I’m guessing they’ve surpassed $10M ARR now…

📈 Their agents now resolve millions of support tickets per month, powering CX for companies like Tripadvisor, ClickUp, HubSpot, Rho, and impact.com.

🚀 At OpenAI, Maven’s agents autonomously resolve 93% of tickets, cut support costs by 81%, and doubled agent productivity.

💎 Across clients, Maven’s AI copilots reduce resolution times by 60% and increase team velocity by 30%.

💰 On June 18th 2025, Maven announced a $50M Series B led by Dell Technologies Capital with participation from Cisco Investments, SE Ventures,  Lux Capital, M13, and E14 bringing their total raised to $78 million.

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