We help SMEs identify the AI worth building, validate the business case, and ship systems that work in production — without wasting months on fragile prototypes or compliance dead ends.
Years of Experience
AI Projects & Solutions
in Computer Science
EU AI Act & GDPR Compliant
We go deep in healthcare and manufacturing — industries where compliance, accuracy, and reliability are non-negotiable.
Medical-AI validation, health-data workflows, and EU AI Act / MDR / IVDR readiness from day one.
Computer-vision quality inspection, predictive maintenance, and workflow automation built for production constraints.
We also work with selected teams in:
From strategy to implementation, we provide end-to-end AI solutions tailored to your business needs.
Strategic guidance to identify AI opportunities and create a roadmap for successful implementation.
Bespoke AI solutions built from the ground up to solve your unique business challenges.
Seamlessly integrate AI capabilities into your existing systems and workflows.
Custom machine learning models for predictive analytics, computer vision, and NLP.
Academic rigor meets production engineering.
Interactive demos showcasing what AI can do for your business - from chatbots to computer vision.
Founded by an AI scientist with a PhD in Computer Science. We bring academic rigor to real-world problems.
We move fast without compromising quality. Proof-of-concepts in weeks, not months.
GDPR compliant by design. Your data stays yours. We can work with on-premise solutions when needed.
Artificial Intelligence is not just technology - it's a competitive advantage. Let us help you unlock its potential.
Latest thinking on AI strategy, implementation, and compliance.
Healthcare AI
Where a healthcare AI system runs is a data-governance decision before it is an infrastructure one. Cloud AI is often defensible when identifiers never leave your control; on-premise earns its keep when they must. Most European healthcare teams end up hybrid.
AI Strategy
An AI readiness audit answers one bounded question and ends with a ranked plan. AI consulting is open-ended access to judgement. Most companies believe they need the second and actually need the first. Here is how to tell them apart.
Manufacturing AI
Buy when the task is standard and your constraint is time. Build when the defect taxonomy is yours or the data cannot leave the plant. Here is how to price the same scope on both sides, and why building too early is the more expensive mistake.
Start with an AI Readiness Audit. Continue with a pilot or Fractional AI Lead once the path is clear.
Sitnik AI treats regulatory constraints as design inputs rather than a review at the end. Every engagement establishes, before any model is built, which tier a system falls into under the EU AI Act, what personal data it touches under the GDPR, and where the two frameworks pull in opposite directions.
In practice that means classifying the system against Annex I and Annex III early, documenting data sources and lineage while the team still remembers them, designing the human oversight point deliberately, and keeping records that can reconstruct any individual decision. The work is grounded in current law: the Digital Omnibus on AI moved the high-risk deadlines to 2 December 2027 and 2 August 2028, and for machine builders the Machinery Regulation applies from 20 January 2027.
This is practical engineering and compliance readiness, not legal advice. It runs alongside your counsel and your notified body rather than replacing either.