SafeIMG is a safety-oriented benchmark for evaluating synthetic-image detection and visual-evidence verification in high-risk public- and personal-safety scenarios. It provides scenario-specific synthetic images generated for assessing how misleading visuals could impact safety and accountability. Researchers and developers can use it to verify and compare image authenticity methods, and to improve robustness of safeguards for trustworthy visual content.

Legalithm is a free, open-source developer toolkit that brings EU AI Act compliance directly into the software development workflow. It classifies an AI system's risk tier under Regulation (EU) 2024/1689 and generates a dated, auditable compliance record. It also supports Article 50(2) transparency duties by watermarking AI-generated content (via C2PA credentials and pixel watermarking) and verifying such marks. A GitHub Action integration fails continuous integration builds when the compliance record drifts from the codebase or from regulatory deadlines, helping engineering teams catch compliance gaps early.

Ster is an open-source framework for intervening in large language model behavior at the level of internal activations to reduce harmful outputs and hallucinations. It helps users improve safety and robustness by enabling targeted controls that affect what the model produces, supporting transparency by making activation-level intervention mechanisms available for inspection and explanation.

SB-Bench is an open source benchmark that evaluates stereotype bias in Large Multimodal Models, using 7 500 real world images across nine social bias categories. It tests whether models default to stereotypical assumptions in ambiguous scenarios and finds that adding vision capabilities to language models consistently increases bias compared with text only baselines. The benchmark, code and dataset are publicly available, offering developers and auditors a reproducible tool for assessing fairness in multimodal AI systems.

Web application that allows organizations to assess their level of maturity in artificial intelligence governance and automatically generate a customized roadmap to meet national and international standards

Fuel iX is an enterprise AI platform that enables organisations to connect their infrastructure to a library of large language models and build, deploy and manage generative AI applications with centralized control and observability.

WasItAI is an image-checker designed to detect AI-generated photos.

An AI-powered speech recognition app that adapts to users' unique speech patterns, facilitating communication for individuals with speech impairments.

Elements of AI is a free online course, offered in Slovakia by AIslovakIA and Comenius University. Created by the University of Helsinki and Reaktor with EU support, it introduces the basics of artificial intelligence through six interactive modules.

The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.

Evaluate input-output safeguards for LLM systems such as jailbreak and hallucination detectors, to understand how good they are and on which type of inputs they fail.

Privacy compliance platform, based on AI/Blockchain, which helps global companies to keep compliant with the data protection requirements.

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

Explainability for Vision Transformers

The open big data serving engine. https://vespa.ai

🧙 A web app to generate template code for machine learning

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Interpretability Methods for tf.keras models with Tensorflow 2.x

Model extraction attacks on Machine-Learning-as-a-Service platforms.

A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.