Dutch LangWatch raises €1M for LLM optimisation

LangWatch, a Dutch startup building the world’s first LLMops (Large Language Model Operations) platform to monitor, evaluate and optimise LLM-powered applications with a scientific approach, has raised €1M in pre-seed funding.

The round was led by Passion Capital, an early stage VC whose portfolio included seed investments in GoCardless, PolyAI and Ravelin. Also participating in the round were Volta Ventures, the Benelux early stage SaaS VC and Antler, the most active early-stage VC firm in Europe.

LangWatch is a comprehensive platform designed to assist AI teams in monitoring, evaluating, and optimizing applications powered by large language models (LLMs). It aims to streamline the development process, enhance quality assurance, and facilitate collaboration among various stakeholders.

Using Stanford's DSPy framework, LangWatch offers a drag-and-drop interface that automates the discovery of optimal prompts and models, reducing the time required for manual adjustments.

The platform enables domain experts from fields such as legal, sales, customer service, HR, health, and finance to participate in the development process, fostering a collaborative environment. In 2024, the global LLM market was valued at approximately $5.72B, with projections estimating it will reach between $123B and $140B by 2034.

Manouk Draisma, co-founder of LangWatch, commented:

“Enterprises worldwide are looking for solutions that provide deep insights, ensure high-quality results, and clearly demonstrate impact to upper management. LangWatch sets a new standard for AI optimization—equipping engineers with powerful tools, including DSPy-based optimizers, to not only quickly identify and resolve issues but also continuously improve quality.

"By integrating these frameworks, LangWatch enables teams to iterate faster and more reliably than ever, allowing companies to deploy competitive AI solutions to production with greater speed and confidence.”

Will Orde, Partner at Passion Capital, added: “LangWatch stands out because they’ve built a platform that makes AI quality control accessible to every engineer and non-technical domain-experts.

"Their hybrid approach—combining LLM prompt optimization with an intuitive, low-code framework—removes a major barrier to deploying reliable AI applications at scale. We were particularly impressed by the founding team’s unique blend of deep technical expertise and commercial acumen, which gives them a distinct advantage in bridging the gap between AI research/development and real-world enterprise adoption.”