Experienced AI specialist for the team – Saidot hired an expert on a permanent basis
Saidot needed deep AI governance expertise quickly to support its growth. The flexible collaboration brought an experienced specialist into the team and led to a permanent hire after eleven months.
Initial situation
Saidot is a Helsinki-based AI governance company whose graph-based, agent-first platform helps businesses and the public sector manage their AI and its compliance. As demand accelerated for enterprise implementations ready for the EU AI Act, Saidot quickly needed deep AI governance expertise to support its growth.
Solution: an AI governance architect as part of the team
AI Talents provided an experienced AI governance architect to join Saidot’s delivery team directly. The architect brought strong experience in enterprise AI architecture, generative AI and compliance frameworks. He worked closely with customers and designed governance solutions to integrate seamlessly with their ML and data environments.
The flexible collaboration continued for eleven months. During this time, the expert’s role developed into a key position, and the collaboration led to a permanent hire. The try-before-hire model gave both parties the opportunity to confirm in practice that the collaboration worked before making the hiring decision.
"Such an experienced AI governance architect is not recruited in an instant, and that is precisely why a flexible cooperation model is valuable to us. AI Talents’ expert was able to get straight into demanding enterprise implementations and works seamlessly as part of our team. In the growth phase, the ability to scale expertise quickly is crucial, and in that respect AI Talents is an important partner for us."
Results during the collaboration
The expert worked extensively on Saidot’s AI governance implementations and delivered results across several areas:
- Automation of regulatory requirements with a Policy as Code approach (EU AI Act, NIST AI RMF)
- Risk management framework and classification tools for AI agents
- Development of MCP servers and scaling the production environment
- Enterprise system integrations into the governance layer
- AI governance agent architecture and deployment
- AI-assisted test automation
- Security assessments and certification readiness (ISO 27001, ISO 42001)
- Evidence management architecture for auditing
Explore the Saidot platform
Would you like to see how Saidot makes AI governance smarter? In Saidot's on-demand demo, Head of Services & Customer Success Iiris Lahti presents the platform's two sides: Saidot Library, one of the world's most comprehensive AI governance databases, and Saidot Governance, which manages AI systems and their risks throughout the entire lifecycle.
Frequently asked questions
What does AI governance mean in practice?
AI governance means an organisation’s operating model for AI systems: the rules, processes and technical controls that ensure the responsible and compliant use of AI. In practice, it covers risk management, monitoring of compliance and the collection of auditable evidence.
How does AI Talents help with EU AI Act compliance?
AI Talents provides senior-level AI governance experts who deliver EU AI Act compliance as part of the client’s team. Our experts translate regulatory obligations into machine-readable rules with a Policy as Code approach and integrate them into the client’s systems. We also provide EU AI Act training and consultancy for demanding sectors such as financial services, healthcare and industry. We deliver both individual specialists to strengthen teams and turnkey implementations.
What is Policy as Code?
Policy as Code means modelling regulatory requirements as machine-readable rules, for example with OPA/Rego technology. The rules check compliance automatically and continuously, making the compliance process repeatable and scalable.
How are the risks of AI agents managed?
Managing the risks of AI agents requires assessing the risk level of each agent and its tools. AI Talents has built a three-stage classification system that combines automated analysis, a deterministic rules framework and expert review. The assessment takes the process context into account: the same tool receives a different risk level depending on whether the agent operates autonomously or the process includes approval stages.
How does the try-before-hire model work?
AI Talents provides an expert to become part of the client’s team on a flexible contract. Both parties can assess how the cooperation works in practice before a hiring decision is made. In Saidot’s case, eleven months of cooperation led to the expert being hired on a permanent basis.