Startup Profiles

Marvelous Is Building AI Infrastructure for Offline Sales

Merve Isler, Founder and CEO of Marvelous, sits down with Ventureport to discuss how AI can help revenue teams find the right rooms, guests and opportunities.

Updated

July 3, 2026 11:39 AM

Marvelous, an AI product company. PHOTO: MARVELOUS

Most B2B sales teams spend their days inside software. They track leads in a customer relationship management (CRM) tool, send emails, build outbound lists and measure every digital touchpoint. Still, many important business relationships move forward in person. A dinner after a conference, a small founder roundtable or a private customer event can do what dozens of cold emails cannot: build trust quickly.  

That is the gap Marvelous wants to fill. The bootstrapped San Francisco-based AI startup is building what founder and CEO Merve Isler calls “Salesforce, but for real life”. Her idea is simple: if companies already use software to manage digital sales, they should also have software to manage the real-world moments that help close deals.  

Marvelous brings data, automation and targeting into in-person go-to-market (GTM) work. It helps B2B sales, revenue, marketing and growth teams plan in-person events such as curated dinners, launch events, mixers, happy hours and conference side events. These formats are already familiar to companies selling to enterprise buyers. The problem is that they are often managed through spreadsheets, venue calls, scattered guest lists and manual follow-ups.  

That creates two problems. First, the process is slow. Teams can spend weeks figuring out who to invite, where to host and how to manage responses. Second, the return is hard to measure. Companies spend heavily on conferences, dinners and private events, yet they often do not have a clear way to know whether an event will influence pipeline before they commit the budget.  

Marvelous wants to pull those pieces into one AI-powered event management platform.  

“Our main target customer is revenue and sales teams,” Isler said. “Because about 40% of deals close in person, but there's no infrastructure built for that—so that's what we do.”  

For Isler, the idea comes from experience. Before starting Marvelous, she worked at Google from Istanbul, managing developer product launches and go-to-market programs across Turkey, Central Asia and the Caucasus. During that time, she helped build more than 100 communities around the world and coordinated thousands of events a year across eleven time zones. The work was fast, local and very manual.

That experience shaped the foundation for Marvelous. Isler saw that building products had become easier, while distribution remained difficult. A startup can now ship software faster than ever. Reaching the right people, in the right setting, is still a different challenge.  

At Google, Isler had to understand how people gathered, communicated and built trust in different markets. A product launch might require developer meetups in dozens of cities, but the right approach could change from country to country. In Kazakhstan, she said, Telegram worked better than WhatsApp. In Afghanistan, Facebook mattered more. Each market had its own habits, and growth depended on understanding those details. Those details and adapt quickly.  

Marvelous grew out of that playbook. Isler saw that offline distribution had patterns, even when it looked chaotic from the outside. The right guest list, the right room, the right timing and the right follow-up could change the outcome of a sales conversation. Most of that knowledge, however, lived in people’s heads. Marvelous is her attempt to turn it into software.  

Inside the platform, a company can start by choosing the kind of satellite event it wants to host: a launch event, a mixer, a happy hour, a brunch, a lunch or a dinner. From there, users can connect their CRM. When Salesforce is connected, Marvelous analyzes contacts and creates relationship scores based on signals such as buying intent, past event activity and how warm a relationship appears to be. If a team also uses an event platform such as Luma or Eventbrite, Marvelous can bring that event data into the picture as well.  

A screenshot of the Marvelous platform. PHOTO: MARVELOUS

The product is built around Maven, Marvelous’ AI assistant. Maven can help plan an event through Slack, iMessage or the Marvelous platform itself. For instance, a user might ask Maven to plan an executive dinner for 18 people within a set budget. From there, Maven can find warm contacts, estimate who is likely to attend, build a guest list, recommend venues, send invitations and run follow-up sequences across email, LinkedIn and SMS. The goal is to let sales teams focus on conversations and closing deals instead of worrying about logistics. Put simply, Marvelous helps a company find the right guests, secure the right venue and understand which event format is likely to work. Instead of guessing whether a US$10,000 dinner will pay off, the company gets a clearer view of the potential return.

A photo of Merve hosting at a recent AI Insiders event. PHOTO: MARVELOUS

AI Insiders, Marvelous’ invite-only network of verified AI and enterprise leaders, is also part of the company’s go-to-market strategy. Rather than asking every customer to build an event from scratch, Marvelous can group several companies that want to reach the same audience into one curated event. Such a setting creates revenue, product feedback and fresh data about what works in different markets. The network spans verticals such as cybersecurity, fintech, robotics, healthcare AI and enterprise SaaS. It now includes members from more than 475 companies, with C-level executives making up nearly half of the community. So far, AI Insiders has facilitated more than 2,000 introductions and contributed to over US$560 million in deals. Isler describes it as one of Marvelous’ strongest go-to-market channels.  

The first AI Insiders event took place at AWS GenAI Loft in San Francisco in April 2026. It brought together 150 curated guests, including AI founders, tier-one investors, enterprise executives and researchers for an evening focused on high-impact conversations and collaboration.  

The timing may work in Marvelous’ favor: Digital outreach is getting louder, and AI will make it easier for companies to send more emails, messages and automated pitches. That may make high-trust in-person conversations more valuable, especially in enterprise sales where relationships take time. At the same time, event budgets need proof. Revenue leaders want to know whether a dinner, roadshow or customer event is worth the cost.  

Marvelous is betting that offline sales will become a measurable category for software. If the company can prove that its relationship scores, event intelligence and AI agent help teams create a stronger pipeline, it could become an important tool for B2B go-to-market teams. The core message of Marvelous is easy to understand: the deals may happen in the room, but data can still power the room.  

Keep Reading

Climate & Energy

How Overstory’s Satellite Data and AI Are Transforming Vegetation Management

What Overstory’s vegetation intelligence reveals about wildfire and outage risk.

Updated

January 15, 2026 8:03 PM

Aerial photograph of a green field. PHOTO: UNSPLASH

Managing vegetation around power lines has long been one of the biggest operational challenges for utilities. A single tree growing too close to electrical infrastructure can trigger outages or, in the worst cases, spark fires. With vast service territories, shifting weather patterns and limited visibility into changing landscape conditions, utilities often rely on inspections and broad wildfire-risk maps that provide only partial insight into where the most serious threats actually are.

Overstory, a company specializing in AI-powered vegetation intelligence, addresses this visibility gap with a platform that uses high-resolution satellite imagery and machine-learning models to interpret vegetation conditions in detail.Instead of assessing risk by region, terrain type or outdated maps, the system evaluates conditions tree by tree. This helps utilities identify precisely where hazards exist and which areas demand immediate intervention—critical in regions where small variations in vegetation density, fuel type or moisture levels can influence how quickly a spark might spread.

At the core of this technology is Overstory’s proprietary Fuel Detection Model, designed to identify vegetation most likely to ignite or accelerate wildfire spread. Unlike broad, publicly available fire-risk maps, the model analyzes the specific fuel conditions surrounding electrical infrastructure. By pinpointing exact locations where certain fuel types or densities create elevated risk, utilities can plan targeted wildfire-mitigation work rather than relying on sweeping, resource-heavy maintenance cycles.

This data-driven approach is reshaping how utilities structure vegetation-management programs. Having visibility into where risks are concentrated—and which trees or areas pose the highest threat—allows teams to prioritize work based on measurable evidence. For many utilities, this shift supports more efficient crew deployment, reduces unnecessary trims and builds clearer justification for preventive action. It also offers a path to strengthening grid reliability without expanding operational budgets.

Overstory’s recent US$43 million Series B funding round, led by Blume Equity with support from Energy Impact Partners and existing investors, reflects growing interest in AI tools that translate environmental data into actionable wildfire-prevention intelligence. The investment will support further development of Overstory’s risk models and help expand access to its vegetation-intelligence platform.

Yet the company’s focus remains consistent: giving utilities sharper, real-time visibility into the landscapes they manage. By converting satellite observations into clear and actionable insights, Overstory’s AI system provides a more informed foundation for decisions that impact grid safety and community resilience. In an environment where a single missed hazard can have far-reaching consequences, early and precise detection has become an essential tool for preventing wildfires before they start.