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

Amsterdam-based Orq.ai has raised €5 million in seed funding as it expands its platform for building and running AI agents in production environments.

The oversubscribed round was led by seed+speed Ventures and Galion.exe. Existing investors Curiosity VC, Spacetime, XO Ventures, xdeck ventures, Waves Capital, and GoldenEggCheck also joined the round.

The latest funding brings total investment in Orq.ai to €7.3 million since its launch in 2022. The company focuses on large organisations that want to move generative AI projects from pilots into live use.

Orq.ai plans to deepen its presence in Europe. It also plans faster expansion in North America, where it already works with customers.

Control layer focus

Orq.ai describes its product as a control layer for enterprise AI agents. The platform spans experimentation, evaluation, observability, a gateway for more than 300 models, and a runtime for live systems.

The company targets engineering teams that need control over how AI agents behave and how data moves across systems. It also targets organisations that face strict data protection and compliance rules.

The push comes as companies across Europe prepare for stricter oversight under GDPR and the EU AI Act. These rules increase attention on data flows, audit trails, and deployment environments for AI systems.

Orq.ai says demand is rising for tools that support this shift from demo projects to production workloads. It says many organisations can show working AI proofs of concept but still struggle with versioning, monitoring, and governance once systems face real users and real data.

Customers include Brand New Day Bank, Afas, Moneybird, Keyrus, and Helloprint. These customers operate across financial services, software and business services.

Backing from industry figures

Several technology executives have joined as strategic advisors and angel investors. They include Sam Bourton, co-founder of QuantumBlack, Adriaan Mol, founder of Mollie, and Daniel Gebler, Chief Technology Officer at Picnic.

Investors say they see a shift in how large companies approach AI deployment. They point to a move away from experiments and towards systems that underpin day-to-day operations.

"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 Kevin Kuipers, Founding Partner of Galion.exe.

Addressing the 'production gap'

Orq.ai positions itself in a segment that some industry observers describe as the AI production layer. This segment includes tools for testing, deploying, monitoring and governing generative AI systems.

According to the company, many large organisations now have working models and internal prototypes. It says the key challenge often lies in scaling these systems under regulatory and operational constraints.

The platform includes an agent runtime that runs agentic systems in production environments. It also includes an AI gateway that offers access to more than 300 models from 17 providers through a single interface.

Orq.ai provides tools for experimentation and simulation of large language models and agents. It also provides evaluation and monitoring features that track performance drift, quality, costs and compliance metrics.

The system integrates with knowledge bases for retrieval-augmented generation workflows. It supports deployments in cloud, hybrid or fully on-premise environments.

Co-founder Sohrab Hosseini said engineering leaders want more structure around the way they manage AI agents.

"Engineering teams don't just need more models; they need the infrastructure to industrialize how agents are built, improved, and deployed," said Sohrab Hosseini, Co-founder of Orq.ai. "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."

End-to-end platform

Orq.ai presents its service as an end-to-end environment for AI agents. It combines prompt and context management, experimentation, deployment, and ongoing optimisation.

The company says this integrated approach reduces the need for teams to stitch together separate tools. It says customers avoid rebuilding foundational components for each new project.

Orq.ai reports that its platform cuts agent development time by 67%. It also reports that it frees more than 10% of engineering capacity in some teams.

Investors argue that this kind of infrastructure will sit beneath a wide range of software products.

"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," said Alexander Kölpin, Managing Director, seed + speed Ventures.

Early backers also say they see a clear shift in priorities among larger customers.

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

Data sovereignty demand

Data sovereignty is a growing theme for both European and US organisations. Regulated industries and public sector bodies face particular pressure in this area.

Orq.ai says its architecture supports sovereignty requirements by allowing enterprises to run AI on their own infrastructure. It says this approach supports data residency rules and reduces reliance on external providers.

The company says US customers receive the same deployment flexibility. It says this helps them build agent-based systems that stand up under production demands.

Orq.ai has recently completed a full rebrand and a redesign of its platform interface. The company now reports more than 100 organisations using its service.

As more engineering teams adopt agent-based architectures, Orq.ai aims to become the default control layer for operating AI agents at scale.