Artificial Intelligence
We build machine cloud assisted learning models for the browser (lightweight) and for the backend (heavy processing) and deploy them on cloud infrastructure: when your needs are quite specific and you require a tailored solution to analyze and extract predictions from your data.
Tailored Machine Cloud-Assisted Learning Models
We design and deploy cloud-assisted machine learning models customized to your unique business challenges—whether it’s lightweight models that run directly in the browser for instant, on-device intelligence, or high-powered backend models capable of handling massive data volumes with complex computations.
By leveraging cloud infrastructure, our solutions combine the speed of local inference with the scalability of server-side processing. Whether you need real-time predictions in a web app or advanced data analysis at scale, we deliver intelligent, cloud-integrated systems tailored to your data and performance requirements.
Let us help you turn your data into actionable insights—efficiently, securely, and at scale.
John Tukey, Statistician
"The greatest value of a picture is when it forces us to notice what we never expected to see."
Benefits
Our models are custom-built around your data and business goals—ensuring more accurate predictions and relevant insights compared to generic, off-the-shelf solutions.
Lightweight models deployed in the browser deliver instant predictions without waiting for server responses—ideal for interactive applications and low-latency environments.
Heavyweight models on the backend can process large datasets, run complex computations, and adapt dynamically as your data grows—powered by flexible cloud infrastructure.
Choose the right balance: fast client-side inference where needed, and deep analysis on the cloud when more power is required—seamlessly connected.
Stats
83%
of enterprises have increased their use of artificial intelligence and machine learning in the last two years.
91%
of businesses using cloud-based ML solutions report faster time to market for new products and features.
65%
of developers now prefer deploying lightweight models in-browser for real-time inference to improve user experience.
80%
of ML workloads will be supported by cloud infrastructure by 2026.