Adaptive ML Taps Palantir, Postman Vets for AI Market Dominance

NEW YORK, NY – April 15, 2026 – In a decisive move to solidify its leadership in the next wave of enterprise artificial intelligence, Adaptive ML today announced the strategic appointments of Marine Boulot as Chief Marketing Officer and Sam Jones as Chief Revenue Officer. The dual hiring of these seasoned executives signals the company’s transition from pioneering a new technology category to aggressively seeking to dominate it.

Adaptive ML, a frontier AI company specializing in Reinforcement Learning Operations (RLOps), is betting that the combined expertise of Boulot, formerly of Palantir and Improbable, and Jones, a veteran of Postman, will be the catalyst that translates its deep technical prowess into undeniable market leadership. The move comes as the company leverages production-scale deployments with giants like AT&T, Manulife, and Deloitte to build a lasting commercial empire.

A Deliberate Play for Category Ownership

The simultaneous onboarding of a CMO and CRO is a calculated strategy, according to the company. It represents a pivotal moment for Adaptive ML as it aims to define and own the Enterprise Reinforcement Learning space it helped create. This strategy, known in Silicon Valley as moving from “category creation to category ownership,” is a high-stakes gambit where a company seeks to become synonymous with the market segment itself, establishing its product as the industry standard.

“Bringing Marine and Sam on board at the same time is a deliberate choice,” said Julien Launay, Co-founder and CEO of Adaptive ML. “This is the moment when category leadership is won or lost — when the revenue infrastructure you build and the narrative you establish determine who owns the space five years from now. Enterprise RL is not a future bet; it is happening in production, at scale, today.”

For deep-tech companies, the journey from a groundbreaking product to a commercially successful one is fraught with challenges. It requires not only technical superiority but also a powerful narrative and a robust sales engine capable of educating a market about solutions to problems they may not have fully articulated yet. Launay’s statement underscores this belief: “We are building to lead.”

The Commercialization Powerhouse Duo

To execute this vision, Adaptive ML has brought in two executives whose careers have been defined by scaling complex technologies into commercial successes.

Marine Boulot joins as Chief Marketing Officer with over two decades of experience navigating high-stakes communications for frontier technology companies. Her resume includes leadership roles at Palantir, Improbable, Altran, and Veolia, where she managed brand and reputation through hypergrowth, IPO preparations, and major M&A activities. Her expertise lies in crafting compelling narratives for technologies with complex stakeholder ecosystems.

“Adaptive ML has the rarest of combinations: genuine technical depth, production deployments at scale, and a category that is still open,” Boulot stated. “The work now is to make that story impossible to ignore, and I feel privileged to be part of this chapter.”

Complementing Boulot’s marketing acumen is Sam Jones, the new Chief Revenue Officer. Jones brings over 15 years of experience architecting go-to-market engines for developer-focused software leaders. Most recently as Head of Enterprise Sales at Postman, he was instrumental in scaling the company’s revenue operations. His career has been marked by a recurring theme: joining companies where the product is ahead of the market's understanding.

“The companies I've been most proud to build are those where the product is genuinely ahead of the market's understanding of it. Adaptive ML is exactly that moment,” Jones said. “My job is to build the commercial engine that matches what this engineering team has already delivered, and the ambition of where we're going.”

Reinforcement Learning Goes Mainstream

Adaptive ML operates at the cutting edge of a specialized field: Reinforcement Learning Operations, or RLOps. Unlike traditional machine learning, which relies on static datasets, Reinforcement Learning (RL) involves training AI agents to make optimal decisions through trial and error, learning from feedback in a dynamic environment. This makes it ideal for complex enterprise challenges like supply chain optimization, dynamic pricing, and automated underwriting.

However, deploying RL at an enterprise scale has historically been complex and cost-prohibitive. Adaptive ML’s core product, the Adaptive Engine, is the world's first RLOps platform designed to solve this problem. It provides the infrastructure for large organizations to build, own, and continuously improve their own domain-specific AI models using open-source technology, all while running on their own secure infrastructure.

From Lab to Live: Validating the Vision with Global Giants

While many AI companies promise future capabilities, Adaptive ML points to trillions of tokens processed in active production deployments as proof of its present-day impact. Its partnerships with major global enterprises are a cornerstone of its claim to leadership.

Telecommunications giant AT&T is using the Adaptive Engine as its reinforcement tuning platform for open-source models across more than 50 use cases. In one evaluation, a smaller, cost-effective model fine-tuned by Adaptive ML demonstrated a 51% win rate against the much larger GPT-4o for tasks involving telecom-specific documents, showcasing the platform's ability to create highly specialized and efficient AI.

Similarly, global insurance and financial services leader Manulife signed a multi-year agreement to use Adaptive ML for fine-tuning its own enterprise AI models. Initial applications are focused on automating underwriting quotes and providing real-time advice to sales professionals, with Manulife’s Global Chief AI Officer, Jodie Wallis, highlighting the platform’s potential to deliver “breakthrough solutions.”

Fortified for Growth and a Competitive Moat

The company’s aggressive strategy is backed by significant financial runway. In March 2024, Adaptive ML raised a $20 million seed round led by Index Ventures, with participation from ICONIQ Capital, Databricks Ventures, and other high-profile investors, reportedly at a $100 million valuation. This capital is fueling the expansion that Boulot and Jones are now tasked with leading.

Adaptive ML’s competitive edge is built on several key differentiators. It champions the use of open-source models, giving enterprises greater control and ownership. Its platform utilizes a technique called Reinforcement Learning from AI Feedback (RLAIF), which automates model improvement and reduces the need for costly human labeling. The company claims this approach can lower the cost of running enterprise AI by up to 90% compared to closed, proprietary alternatives.

By hiring a CMO and CRO with proven track records in scaling deep-tech ventures, Adaptive ML is making a clear statement. The company is leveraging its technical foundation, validated enterprise success, and substantial funding to build a commercial juggernaut poised to define the intelligence layer of the modern enterprise.