Bridging the gap between Research and Industrial Application. We deliver machine learning solutions designed for scalability, interpretability, and real-world impact.
Based in London, Fanis AI is an independent R&D laboratory, implementing solutions in the field of AI. We specialize in high-complexity challenges: from denoising scientific imagery and running computer vision on the edge to high-end multi-modal AI Agents. If the problem is deemed "too hard" or the data "too noisy" for standard APIs, that is where we begin.
Hybrid architecture combining deep learning perception with physics-based constraints validation. Systems for 3D scene reconstruction and object tracking in dynamic environments using multi-modal sensor fusion.
Optimizing hybrid AI architectures for edge and on-premises deployment. Ensuring real-time performance without sacrificing accuracy.
Hybrid video analysis systems combining stochastic pattern recognition with deterministic validation. Real-time event detection pipelines with hardware acceleration.
We engineer advanced multi-modal Agentic AI achitectures intgrating text, images, video, audio and sensor measurements in enterprise environment.
Robust pipelines for training and deployment: from microservices to cloud-native deployments. We ensure your AI systems are scalable, reliable, and continuously monitored.
Numerical methods and statistical modeling for noisy domains. We design and apply custom models to solve signal processing problems where standard algorithms fails.
Whether you are a startup requiring a custom algorithm or an enterprise seeking to audit existing ML infrastructure, we provide the technical depth required to succeed.
Proven capabilities in Computer Vision, Generative AI, and Agentic AI Enterprise Systems.
Design and development of an AI-powered agentic chat that directly interacts with enterprise SQL databases. This tool simplifies complex query generation, enabling non-technical executives to effortlessly access and interpret sophisticated data insights without learning SQL.
Research on applications of diffusion models for denoising electron backscatter diffraction (EBSD) patterns - it is the first successful application of diffusion models to EBSD pattern restoration. The model incorporates a mechanism to distinguish real signal from noise, helping to prevent hallucination. This enables the study of materials that are unstable under electron microscopy, such as components for solar energy applications.
Development of an iPhone application providing real-time feedback on boxing movements using on-device Computer Vision. We engineered one of the first video AI insight extraction models (combining event detection and pose estimation) running entirely on an iPhone at 60 fps.
Tackle the impossible together - let's design AI solutions that push the boundaries of what's achievable in your domain.
Our collaboration model focuses on:
• Developing domain-specific computer vision solutions through partnership
• Co-creating calibration-as-a-service SDKs through joint development
• Building scalable enterprise AI solutions as a strategic partner
• Advancing scientific imaging research through joint innovation