Orq.ai raises EUR €5m to industrialise enterprise AI agents

Amsterdam-based Orq.ai has raised €5 million in seed funding as it targets one of the toughest problems in corporate artificial intelligence: moving agent-based systems from controlled demos into reliable production use.

The oversubscribed round was led by seed+speed Ventures and Galion.exe, with participation from existing investors Curiosity VC, Spacetime, XO Ventures, xdeck ventures, Waves Capital and GoldenEggCheck. The latest funding brings the company's total capital raised since its 2022 founding to €7.3 million.

Several technology executives joined the round as strategic angel investors and advisors, including Sam Bourton, co-founder of QuantumBlack at McKinsey, Adriaan Mol, founder of payments firm Mollie, and Daniel Gebler, Chief Technology Officer at online supermarket Picnic.

Regulatory pressure

Orq.ai is building a control layer for enterprise AI agents. It offers infrastructure for experimentation, evaluation, and observability, a gateway to more than 300 models, and a runtime environment for live production use.

The company is expanding as European regulators introduce tighter rules for data use and artificial intelligence. The General Data Protection Regulation already governs the processing of personal data, and the EU AI Act will impose specific obligations on AI systems.

Orq.ai says engineering teams are looking for ways to maintain control over data flows, model behaviour and deployment environments under these conditions. The company reports growing demand from European and US clients for AI systems that can withstand real user traffic, regulatory scrutiny, and operational risk.

Its customers include Brand New Day Bank, Afas, Moneybird, Keyrus and Helloprint. The platform is now in use at more than 100 organisations.

Alexander Kölpin, Managing Director at seed+speed Ventures, said enterprises face an inflection point in how they run AI across their software stacks.

"AI agents are becoming a foundational layer of enterprise and B2B software, much like cloud infrastructure in the last technology cycle. Companies will need a reliable way to orchestrate, govern, and scale these agents across operations, and Orq.ai is building the platform that will enable that shift."

Kevin Kuipers, Founding Partner at Galion.exe, said companies are moving rapidly past early-stage trials.

"Enterprises are no longer experimenting with AI for curiosity. They want to implement it fast, but most of them are stuck passing real systems into production. We believe Orq.ai is the solution for their needs, as it for us. it accelerates our development process daily and is even used by non-technical profiles. Orq.ai's unified agent lifecycle platform shortens iteration time, reduces friction and brings stability to deploy agents at scale," said Kuipers.

Production bottleneck

Many large companies can now demonstrate generative AI services in controlled settings. Few run them reliably in complex production environments. Orq.ai describes this as a production gap, where version control breaks down, monitoring is incomplete, and governance processes remain manual.

The firm positions its platform as a single environment for the full lifecycle of AI agents. This covers prompt and context design, experimentation with different models, deployment into production systems and ongoing monitoring and optimisation.

Core elements include an agent runtime that runs agentic systems in production, with a focus on consistent behaviour and audit trails. It also includes an AI gateway that aggregates access to more than 300 models from 17 providers through one application programming interface.

Other functions include tools for experimentation and simulation, evaluation and monitoring across metrics such as performance drift, quality, costs and compliance, as well as integrations with knowledge bases that support retrieval-augmented generation. The platform runs on different infrastructure setups, including public cloud, hybrid and fully on-premise environments.

Co-founder Sohrab Hosseini said engineering leaders want more structure around how they create and maintain agentic systems.

"Engineering teams don't just need more models; they need the infrastructure to industrialise how agents are built, improved, and deployed," said Hosseini. "They want clarity on how agents behave, how data moves through their systems, and how to stay compliant as the regulatory landscape evolves. We provide them with the harness to have this control."

Time and cost focus

Orq.ai says its approach reduces agent development time by 67% and frees up more than 10% of engineering capacity. Teams avoid recreating shared components for each new AI project and can reuse evaluation, monitoring and governance workflows.

The company has introduced a feature called Agent Studio alongside its runtime. This lets teams configure agent behaviour, workflows and decision rules while the platform manages execution behind the scenes.

Orq.ai states that this setup supports use by both software engineers and non-technical staff. It frames this as an advantage for organisations that want business teams to work directly with AI-driven processes under controlled conditions.

Herman Kienhuis from Curiosity VC said clients are shifting their priorities as adoption spreads.

"Leading enterprises have moved past AI experimentation. Their focus now is production," said Kienhuis. "Orq.ai supports that transition by reducing iteration time, cutting operational friction, and giving engineering teams a stable foundation for scaling agents."

Data sovereignty

Tighter governance requirements are influencing how companies design their AI stacks, especially in regulated industries and the public sector. Orq.ai highlights what it calls a sovereignty-ready architecture that allows customers to run AI on their own infrastructure. It also aims to support data residency rules and reduce reliance on external providers.

The company says this flexibility is essential for both European and US clients who want resilience and control as they move AI agents into live environments.

Orq.ai has undergone a full rebrand and redesign of its platform experience as it focuses on the role of AI control layer in enterprise systems. The firm expects demand for agent-based architectures to grow as production AI matures and as companies standardise how they operate AI agents at scale.