A commitment to innovation and sustainability
Our personnel bring over a decade of AI/ML engineering and 10+ years of experience delivering EU‑funded initiatives, helping organisations build AI that is private, secure, resilient, and ready for real‑world decisions.
Expertise and experience
Program and technical leadership
Project coordination, quality assurance, and risk management.
Proposal leadership
Consortia building and EU‑funded proposal development.
System‑level AI engineering
Architecture and orchestration of large‑scale, safety‑critical AI pilots.
AI/ML modelling and deployment
Open‑source stacks (e.g., TensorFlow, scikit‑learn, Prophet, PyOD) with robustness and monitoring baked in.
Federated learning
Design and rollout with frameworks such as Flower, TensorFlow Federated, and LEAF to keep data local.
Privacy‑preserving AI
Differential privacy, secure aggregation, and minimal‑exposure data patterns.
Secure and robust analytics
Adversarial robustness, data integrity controls, model resilience testing, and post‑deployment safeguards.
IoT and critical infrastructure
Predictive maintenance and monitoring with strong safety and reliability guarantees.
Energy/resource‑efficient AI
Compact, edge and on‑prem models that balance performance, cost, and risk.
What we focus on
Our design choices in the current and emerging world of general purpose, extreme-scale and costly models with vast capabilities – but also a wide spectra of risks and vulnerability surface – we aim at making the right balance between generality of model capabilities, sizes and deployment costs, and vulnerabilities and emergent risks, to harness the power of generative Ai will keeping systems safe , private, and secure, for the application at hand.
We also act as an evaluator and capabilities and risks-test designer, verifying whether planned or deployed AI systems meet expectations on safety, privacy, security, fairness, and reliability, and we provide practical hardening plans when gaps appear.
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How we help
- Trust and safety: Confidential analytics, robust and secure modeling, and federated learning that keeps sensitive data at the source.
- Independent trustworthiness, capabilities and risk assessments: Structured evaluations across privacy, security, bias, safety, and reliability.
- Remediation and hardening: Clear diagnoses and targeted fixes to close vulnerabilities, curb bias, prevent data leakage, and strengthen model robustness.
- Responsible deployment: Guidance on governance, risk management, model oversight, and safe integration into human and automated decision flows.
- Help for regulated use: Support for EU AI Act–aligned practices, data residency requirements, and on‑prem or hybrid architectures when cloud export is constrained.
- Exclusive access to design insights.
Why choose TurbeLytics
Deep EU program delivery: 10+ years leading and coordinating EU‑funded projects with a strong track record in technical leadership.
R&D rigor: Academic‑grade methods, publications in top venues, and recognition by the EU’s Innovation Radar.
Safety‑first engineering: System thinking, QA, and risk management embedded across the AI lifecycle.
We design, test, and validate trustworthy AI—privacy‑first analytics, secure and robust models, and distributed/federated learning—so you can deploy with confidence.