About Aimable
We build the governance foundation that ensures information does not leak, that policies are enforced and that AI usage meets regulatory requirements.
Our Mission
Aimable makes AI safe and practical for any company that needs control over data and compliance. We build the governance foundation that ensures information does not leak, that policies are enforced and that AI usage meets regulatory requirements.
AI creates value only when companies can trust both the handling of their data and the quality of the output. Aimable enables that level of control and reliability.
What We Are Trying to Achieve
Aimable provides the baseline infrastructure for governed AI so organisations in any region can use AI without risking data exposure or violating compliance obligations. This applies to all companies, not only those with highly sensitive information.
Data stays under the organisation's control. Policies apply to every interaction. Usage is observable and auditable. Model choice does not diminish sovereignty. Guardrails and controlled data context improve consistency and reliability in AI outputs.
By embedding governance into the infrastructure, Aimable aligns innovation, compliance and output quality across jurisdictions.
Core Ideas Behind Aimable
These are the principles that guide what Aimable builds and why it exists.
Governed by default
AI operates within defined policies. Every interaction is controlled, traceable and accountable.
Data stays under control
Companies retain ownership and oversight of their information. Raw data remains in trusted environments, reducing the risk of leakage for any type of business.
Model choice with sovereignty
Teams use the most suitable model per task without giving up control over data, behaviour or outputs. Selecting the right model improves usefulness while maintaining governance.
Transparency as a requirement
AI interactions are traceable for compliance and security. Authorized teams can audit what data was accessed, how it was used and how outputs were generated, within the organisation's governance rules.
Practical adoption
AI is usable by employees and developers without creating unmanaged risk. Guardrails, policy enforcement and governed data context improve output quality and reduce operational risk. Tools fit enterprise constraints and developer workflows.
Founding Team
Ian Zein, CEO
Former co-founder and CEO of Sentia, a 600-person international cloud company focused on mission-critical IT.
Arjé Cahn, CPO
Former co-founder and CTO of Hippo and later Chief Product Officer at Bloomreach, a Silicon Valley Unicorn.
Bart Evers, CTO
Former co-founder of Gillz, now part of VINCI Energies, with extensive enterprise engineering and delivery experience.
Ludger Visser, Founding & Lead Engineer
Senior engineer with deep AI, Machine Learning, Data and coding experience.
Join Us
We're building the future of enterprise AI. If you're passionate about unleashing AI while giving back control to the organization, we'd love to hear from you.