What we do
Frontier AI runs on demo culture. A polished prototype, a launch tweet and then the accountability conversation never happens. “Move fast and break things” is a defensible philosophy until the thing that breaks turns out to be your production environment, your compliance posture, or the trust of your customers.
We build the other kind. Enterprise AI that is reliable, explainable, governed, and ready for the conditions that actually exist in large organizations with regulatory scrutiny, operational complexity, and the requirement that outcomes be measurable and defensible. Predictability is a feature here, and control is a requirement.
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our AI FACTORY APPROACH
Analysis of 177 enterprise agentic AI deployments reveals that ad-hoc, project-based deployment models suffer from high failure rates (69%), extended time-to-value, and unsustainable governance overhead. The Agentification Factory model replaces this with a systematic and repeatable production pipeline — achieving a 65% success rate, 40–60% faster time-to-value, and a verified net ROI of 21% through the compounding ROI Flywheel effect.
We created a structured method for assessing automation potential and setting agentification targets that reflect what AI can actually deliver today. That means working with the real limitations of current AI, not vendor benchmarks.
In this whitepaper, we explore eight agentic governance models, providing a compre‐
hensive comparison across critical dimensions such as scalability, operational cost, auditability, and suitability for regulated environments.
By treating agent deployment as a continuous
production pipeline rather than a series of discrete projects, the factory model dramatically reduces the marginal cost and risk of each new deployment.
our Services
Ambition without structure is just a roadmap to regret. We translate AI vision into an executable operating model that covers governance, platform architecture, and delivery design, so that when scale arrives, it does not bring chaos with it.
Before anything gets automated, we map how work actually moves through your organization, where friction accumulates, and where agentic execution would create genuine leverage rather than cosmetic efficiency.
We design AI stacks with explainability, observability, access controls, data lineage, and auditability treated as structural requirements from the first line of architecture, not as features bolted on after an audit request arrives.
AI without lifecycle discipline is allowing technical debt to build up. We implement a full AI Software Development Lifecycle covering design, validation, deployment, monitoring, retraining, and retirement, because a model that nobody owns eventually becomes a model that nobody trusts.
We build the infrastructure for your process operators that measures real performance, bias, drift, control effectiveness, and business value against your data, your processes, and your definition of what good actually looks like.
We design or implement your control frameworks that embed accountability, traceability, human oversight, and policy enforcement into every stage of the AI lifecycle, covering model approvals, vendor risk, audit readiness, and regulatory alignment.
We secure enterprise AI through identity controls, data protection, continuous monitoring, red teaming, prompt injection defense, and access governance, built into operating models that are designed to hold under pressure.
We help organizations move from confused experimentation to AI that people trust, use, and benefit from, without dismantling everything that made the organization functional in the first place.
our research
We conduct fundamental research into agentic AI at enterprise scale. We analyse success stories, create frameworks that hold up under pressure, and we build AI-models for enterprise AI that holds up under scrutiny. Our research is published in journals and preprint servers for the community to use.
We created a structured method for assessing automation potential and setting agentification targets that reflect what AI can actually deliver today. That means working with the real limitations of current AI, not vendor benchmarks.
The OCG framework connects operating cadence, governance discipline, and delivery execution into a single enterprise model. Built for organizations that need clear AI ownership, decision velocity, and real delivery rhythm rather than accountability structures that exist only in org charts.
Most AI programs measure activity. We measure value. The Roundtrip Value model links investment, adoption, operations, and business outcomes into one closed loop, making visible where value is created, where it leaks, and what is actually worth scaling.
EIGENVECTOR BLOGS
An intro to Dutch tokenomics If you are responsible for running an agentification program, you will have learned the hard way, how fragile your ROI is. Even though token prices dropped 99.7% over the last few years, the bills that the frontier AI labs have sent to our companies have tripled, and that is because…
In Greek mythology, there was this guy, Atlas who was condemned to hold up the sky. Not the earth, as the popular version goes, but the celestial sphere itself. The distinction is subtle and mostly irrelevant, except that it captures the exact energy of building a research intelligence platform for enterprise agentic AI that no…
meet our management team
Henk de Koning
Henk is a rare hybrid of engineer and creator who moves between code, systems, and ideas with the ease of someone who never accepted that boxes should exist in the first place.
Henk
Chief Architect
James Johnson
Part relationship-builder, part mathematician, part drummer, part rockstar. James is what happens when charisma develops analytical precision
James
Customer Success
Marco van Hurne
AI model researcher, Agentification factory specialist, builder of frameworks, collector of gadgets, and loyal servant to a dachshund
Marco
AI Factories
An AI Factory is a repeatable operating model for designing, deploying, governing, and scaling AI products, automations, and agents across the enterprise.
Through explainability, telemetry, governance controls, lifecycle management, and evidence-based monitoring.
Yes. We analyze workflows, controls, bottlenecks, handoffs, and waste before introducing automation.
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Both. We design strategy, architect systems, build platforms, automate workflows, and support scaling.
Yes. We are vendor-neutral and integrate AI into the environments where work already happens.
We use our Roundtrip Value model to connect investment, operations, adoption, and measurable outcomes.
With a discovery session focused on opportunities, risks, readiness, and fastest routes to value.
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Schedule a free consultation focused on opportunities, risks, readiness, and reliable routes to value
EIGENVECTOR 