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
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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.
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.
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.
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A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
April 24, 2026 10:53 AM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.