our services

Software consultancy

Software design, development, analysis

DSP and Machine Learning

Digital Signal Processing and Multimedia software, applied Machine Learning consultancy

Hardware Acceleration

Hardware acceleration with Xilinx FPGA hardware and tools, also Embedded system design

Teaching

Teaching courses about Digital Signal Processing, Machine Learning, Artificial Intelligence and Web based cloud design.

our PRODUCTS

MRadio

Audio stream analyzer all over Italy. It uses Mooseka service for audio tracks recognition.

Mooseka

Audio analysis system based on cloud which generates musical report and extracts high level features.

MuseBox

FPGA Machine Learning based system for real-time AV Broadcasting applications

Our selling points

Research

Bringing technological innovation on signal recognition. Doing scientific researches regarding multimedia recognition and feature extractions

Development

Realizing multimedial recognition systems completely automized, also accelerated system on FPGA

Focus

Following the customer step by step for system integration

business-camera-coffee

Public Relator & Commercial Director

Chief Executive Officer &  Chief Technical Officer

Frontend developer & Web designer

Backend developer

Backend developer & Database Maintainer

Technological consultant

Graphic designer & Frontend developer

Partner Università degli Studi di Verona

SW engineer, mathematical modelist for physical simulation

Artificial Intelligence Consultant

 IT developer, backend developer,
system engineer and cloud system developer

CMS Senior developer, System Engineer, Software Engineer

Monitored Streams
Classified Media
Code Lines
Cups of Coffee

our articles

PYNQ logo
FPGA

Advanced PYNQ example on GitHub

Pynq is a famous framework that allows programmers to directly work with FPGA using Python language, which is very intuitive, so let’s take a look at it. When we want to accelerate a specific software portion, it is generally difficult to interface to it correctly, because you have to synchronize the CPU (generally referred to

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FPGA

AI Edge Platform on ZynQ FPGA

Artificial Neural Networks Artificial neural networks (ANN) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems “learn” to perform tasks by considering examples, generally without being programmed with task-specific rules; so you can get it to learn things, recognize patterns, and make decisions in a “human-like” way. The patterns recognized are numerical,

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Alveo U200 for SPS 2019
Digital Twin

Digital Twin with Xilinx Alveo™ and Vitis™ at SPS trade show (SPS Drives 2019).

https://www.linkedin.com/pulse/digital-twin-xilinx-alveo-vitis-sps-trade-show-giulio-corradi-1f/ After 30 years of SPS IPC Drives, the trade show changed the name into SPS – smart production solutions reflecting the digital transformation that occurs in automation technology. Digital Twin (DT) in relation to Cyber-Physical-Systems (CPS) are among the main themes of this digital transformation anticipated by the Industry 4.0 initiative. According to DirectIndustry e-magazine interview

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our abilities

Cloud Services
90%
Deep Neural Network
80%
Digital Signal Processing
95%
Programming
99%
FPGA Acceleration
90%

our technologies

Xilinx VERSAL™
Xilinx ALVEO™
Xilinx PYNQ™
Xilinx ZYNQ UltraScale+
Xilinx VITIS™
Xilinx VIVADO™
Xilinx SDAccel™
VIVADO HLS™
Python
NodeJS
WordPress
Amazon AWS
Google Cloud Platform
Cassandra DB
MariaDB
Librosa
Ansible
Bootstrap
Electron
Ionic

our partners

Xilinx Inc. – Acceleration Program

Azure Microsoft for startup

Università degli Studi di Verona

ZeroMoneta Records

Latlantide

Shadows Light

Vittek Records

Telegraph Road Studio

Me&U Records Music

Athena s.r.l. Rational Seed

HDEMY Group

Nuova Accademia del Design