About Machine Can See


We build computer-vision systems for real-world infrastructure—where reliability, safety, and accountability matter.

Our flagship product is GateGuardX. We also develop visual AI solutions for parking and traffic analytics.

May 2019

MCS

All in on Visual AI

We started Machine Can See to build production-grade computer vision for physical environments—systems that work reliably outside of controlled lab conditions.

July 2020

Innovation Fund of Serbia

Innovation Fund support (pre-seed, equity-free)

Machine Can See secured an equity-free pre-seed investment of 115k EUR from the Republic of Serbia’s Innovation Fund.

September 2020

First Employees

First hires

We hired our first employees and started building in-house R&D and engineering capacity.

April 2021

Whitepaper #1

Whitepaper #1
Parking Occupancy Prediction using Computer Vision with Location Awareness

A proposed approach for outdoor parking occupancy using computer vision and smart edge devices, combining new data streams to build a 3D understanding of the environment and identify available spaces.

May 2021

X-Europe Programme

X-Europe program

Selected as one of 27 startups (out of 124 applicants) to participate in the program, supporting our mission to bring Visual AI to infrastructure and smart-city use cases.

Learn more →

June 2021

Patent Submitted

Patent Submitted
Method and system for prediction of objects in the space in real-time via 3D replica

Machine Can See’s patent aims to improve object prediction using camera imagery, focusing on objects such as vehicles, buildings, and roads. The system generates a vector-based representation of each object through a neural network, stores it in a database, and uses it to create a 3D simulation of the observed environment.

By incorporating physics-based models, the system increases accuracy and realism, enabling more precise predictions of real-world scenarios.

Find out more about our patent →

March 2022

Prototype - Parking Lot

Prototype ready

We built and tested an outdoor-ready prototype, validating key performance and deployment assumptions.

May 2022

Whitepaper #2

Whitepaper #2
3D Vehicle Pose Estimation from an Image Using Geometry

An approach to estimating 3D object orientation from a single image using geometry-based methods.

Find out more about our whitepaper →

June 2022

Vladan Damjanovic

First major paying client (US)

Landing our first major paying client in the US validated real market demand for our technology and deployments.

2026

Future

Today

We build and deploy production-grade visual AI—starting with GateGuardX and expanding into parking and traffic analytics.

Team key members

We’re a product-focused engineering team building applied computer vision—from edge deployments to cloud dashboards.

Vladan Damjanovic
Vladan Damjanovic
Co-Founder & CEO

Srdan Vukmirovic
Srdan Vukmirovic, PhD
Co-Founder

Milan Bratic
Milan Bratic
Developer

Advisors

We collaborate with experienced researchers and industry experts in Visual AI and applied machine learning.

Dubravko Culibrk
Dubravko Culibrk, PhD
AI Scientific Advisor

Professor at the University of Novi Sad. PhD in Computer Engineering (Florida Atlantic University).

Works in Visual AI and neural networks. NVIDIA Deep Learning Institute University Ambassador.

Machine Can See

We build computer-vision systems for real-world infrastructure.

Nikolajevska 2, Novi Sad
Serbia

info@machinecansee.com
+38163593274

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