The Public Call under the aforementioned programme line was open from 23 April to 16 June 2025 and attracted significant interest from innovative companies, with a total of 86 applications submitted.
Following the administrative review, 66 applications were referred for international evaluation, with three independent experts assigned to each individual project. The experts were selected from the Innovation Fund’s evaluator database, based on the required expertise and the content of each project. Upon completion of the first evaluation round, 44 project teams met the defined passing threshold and proceeded to the second round of evaluation.
In the second round, the project teams presented their projects in person and answered questions from the three-member international Expert Committee. Based on the combined scores from both evaluation rounds, 14 projects were recommended for funding: 10 projects in the field of information and communication technologies, 3 projects in the field of energy and sustainable environment, and 1 project belonging to other fields.
The total budget initially allocated for this Public Call amounted to EUR 1,200,000.00. However, due to the larger number of high-quality projects recommended for funding by the Expert Committee, the budget of the Public Call was increased to EUR 2,435,454.15.
The difference between the initially available and contracted funds was provided through the Strengthening Existing Innovation Fund Programmes initiative, within the Innovation Ecosystem Development Plan, using funds from the Investment Programme of Special Importance for the Economic and Economic Interest of Montenegro – Proposal for 2025.
The programme line supported projects whose technological maturity was beyond the proof-of-concept stage but which were not yet ready for the market, i.e. projects with a Technology Readiness Level (TRL) ranging from TRL 5 to TRL 8, corresponding to the experimental development stage.
List of approved projects:
Fund recipients
Project name
Vatrogon
Project description
Vatrogon – Development of an Advanced Autonomous Drone-Based Software System for Early Fire Detection and Prevention Using Artificial Intelligence and Real-Time Environmental Data Analysis Vatrogon is an advanced platform for early fire detection and rapid response, combining autonomous monitoring with human-supervised interventions. Using artificial intelligence and a fleet of drones, the system continuously monitors fire-prone areas and independently identifies the first signs of fire. Upon detection, the system automatically deploys specialized firefighting drones to the location and delivers data to operators in real time, enabling them to assess the situation and remotely initiate precise firefighting actions.
Project name
PatchMark: Patchable Audio Watermark Resistant to Cloning
Project description
PatchMark is a project aimed at making AI-generated audio easy to verify and harder to misuse. It is based on a “patchable” watermark—a small, inaudible digital signature that is: Embedded in every audio file produced by a voice AI system. Upgradable – if the watermarking standard changes, owners can update the small patch instead of re-watermarking thousands of files. Resistant to voice cloning and compression. Instantly verifiable – anyone can use a simple detector to confirm who created the file and whether it has been modified.
Project name
Innovative Smart Mooring System for Boats
Project description
The innovative smart berthing system provides an automated, efficient, and safe solution for mooring and unmooring vessels at ports, particularly useful under changing weather conditions and high waves. This unique and patented system offers significant advantages over existing berthing methods by increasing safety, reliability, and operational efficiency during mooring and unmooring procedures. Constructed from durable components resistant to marine environmental conditions, the system is highly efficient to manufacture and maintain.
Project name
BOOST2 Project
Project description
The BOOST2 Project aims to revolutionize the management of EU-funded grants by creating a comprehensive, user-friendly software platform that ensures strict compliance with complex regulatory requirements. Designed for small and medium-sized organizations—such as non-governmental organizations, local governments, and public institutions—the BOOST Project platform simplifies and automates key processes, including procurement, financial and narrative reporting, and results monitoring. The platform features predefined workflows, automated AI-assisted document generation, and narrative reporting, all designed to ensure compliance with EU regulations such as PRAG and GDPR.
Project name
AI Agent for Automating Content Updates and Management in LMS Systems
Project description
ZUNO Games plans to develop and commercialize an AI-based software agent that automatically detects outdated information in LMS (Learning Management System) platforms and suggests updates based on changes in the company’s internal documents, including policies, procedures, and regulatory requirements such as GDPR, ESG, and AML. The solution is intended for organizations subject to stringent regulatory requirements—particularly in the banking, energy, pharmaceutical, and public sectors—where maintaining the compliance of educational materials is challenging and time-consuming.
Project name
DigitalKiosk
Project description
The project aims to provide users with access to financial services through a new module of the Digital Kiosk mobile application, offering the following functionalities: DPI – Digital Payment Institution; the ability to pay for goods and services digitally, including through a bank account as a means of payment, rather than exclusively by payment card; e-commerce services, enabling the company Business Integration and Business Intelligence (2BI) to accept card payments independently, without a bank acting as an intermediary; acceptance of card payments through physical POS terminals developed and owned by 2BI; issuance of a digital-only payment card, without a physical card, in cooperation with VISA International and MPM d.o.o. (Cosmetics Markets).
Project name
Presto Application – Development of Advanced Features
Project description
Presto is a financial application designed to help users simplify and optimize the management of their personal finances. Rather than simply providing an overview of their current balance, users will be able to allocate funds into customized “spaces”—such as savings, expense accounts, or travel—and set goals for larger expenditures, such as vacations or a down payment on a home. The application provides a visual overview of users’ financial situation and progress, helping them plan clearly and efficiently. To improve access to credit, Presto will also enable microloans within the application, in partnership with a commercial bank.
Project name
Agentic AI for Financial Services
Project description
The “Agentic AI for Financial Services” project is a groundbreaking initiative designed to transform the financial industry through the use of advanced AI technologies. The key objective is to develop AI agents capable of achieving human-level accuracy while operating significantly faster, representing a digital workforce capable of accurately and efficiently replicating human tasks. At the core of the project is the development of four specialized AI agents covering key financial operations: a financial analysis agent, a regulatory and compliance agent, a digital customer onboarding agent, and a loan approval agent. These agents will operate both autonomously and in coordination with one another, simplifying complex processes, eliminating manual work, and accelerating service delivery without compromising accuracy.
Project name
CRNOGOČI: AI-Powered Tool for Accelerated Software Development
Project description
The aim of the project is to develop and implement an artificial intelligence-based software assistant that will significantly enhance the company’s internal innovation capabilities, employee knowledge transformation, and market competitiveness. The tool will cover all stages of software solution delivery through an agent-based system organized around three key functional areas: A group of agents that guide users through the development stages—research, design, development, and testing—providing clarity and a structured process in line with best practices; Agents that directly execute development tasks through code generation and processing; and Agents that verify the completeness and quality of input documentation, as well as compliance with relevant standards, before moving on to the next stage.
Project name
Sentiment Scope – AI Software for Comment Moderation and Sentiment Analysis
Project description
Sentiment Scope is an AI-powered tool that automates comment moderation for online portals. In addition, it serves as a tool for analyzing market sentiment across digital channels. Comment moderation involves the process of reviewing and managing user-generated comments on online platforms, including approving or rejecting them. This process is currently carried out through manual moderation, involving the monitoring, filtering, or removal of comments that are inappropriate, harmful, or constitute hate speech. The aim of comment moderation is to maintain a safe and positive environment for all users.
Project name
PAIDT – Trading Based on Intelligent Price Movement Detection
Project description
The system combines a unique adaptive AI model with a modular architecture to meet the needs of B2B and B2B2C clients. PAIDT enables seamless integration and operates under a Value-as-a-Service (VaaS) model, in which clients pay exclusively for verifiable value delivered. The “Trading Based on Intelligent Price Movement Detection – PAIDT” project represents the strategic evolution of the company’s PAIDT v4 system, which has reached a Technology Readiness Level (TRL) of 7–8.
Project name
SolarCastAI – Intraday Solar Power Generation Forecasting System
Project description
SolarCastAI is an advanced platform for intraday forecasting of solar power generation that combines multiple data sources—including SCADA systems, plant specifications, weather APIs, satellite data, and 360° cameras installed on-site. By using machine learning and computer vision, the system provides more accurate short-term generation forecasts by tracking cloud movement, the position of the sun, and atmospheric optical density. The aim is to optimize participation in the intraday market and reduce imbalance penalties through the direct integration of forecasts into trading decisions.
Project name
GoGrant.me – Innovative AI-Supported Software for Online Calls and Grants
Project description
The aim is to automate up to 95% of tasks throughout the grant lifecycle—from application submission and verification to preliminary evaluation—enabling staff to focus on strategic oversight and ethics. In essence, the system functions as an “army of digital public servants,” i.e. a network of AI agents, each performing specific roles in grant management, while all agents are coordinated to streamline workflows and improve decision-making. This will allow grant managers to focus on high-value tasks, such as refining strategies, providing support to applicants, and making final funding decisions.
Project name
Intelligent System for Real-Time Optimization of Aluminum Electrolytic Cell Management
Project description
The aim of the project is to revolutionize the management of alumina feeding in the aluminum electrolysis process through the development and implementation of an AI-based adaptive process control system. The innovative approach uses real-time monitoring of the rate of electrical resistance decrease immediately after each dosing operation. A rapid decrease in resistance indicates a low alumina concentration, while a slow decrease or even an increase in resistance suggests that the bath is oversaturated. By interpreting these dynamic resistance profiles, the AI system intelligently adjusts the number of piercing and dosing cycles, as well as the duration of the cycle intervals—shortening the intervals following periods of low concentration and extending them when signs of oversaturation are detected. The expected results include improved stability of electrolytic cells, a reduced number of anode effects, enhanced energy efficiency, and improved overall environmental performance.
