CRIM —Support

Q: How much funding can be received?

There is no informations about how much funding can be received.

Q: What is the deadline to apply?

The deadline to apply is not specified.

Q: Is the CRIM —Support a grant, loan, or tax credit?

CRIM —Support is a Expert Advice

Q: Who are the financial supporters of the CRIM —Support?

CRIM —Support is funded by Computer Research Institute of Montreal (CRIM)

Q: Who is eligible for the CRIM —Support program?

Eligibility criteria are not specified.

Q: Who can I contact for more information about the CRIM —Support?

You can contact Computer Research Institute of Montreal (CRIM).

Q: Where is the CRIM —Support available?

The CRIM —Support program is available across Canada.

Last Update: July 22, 2025

Canada

Support for technological innovation projects

At a glance

Eligible Funding

No Condition

Timeline

Open Date : August 17, 2023

Financing Type

Expert Advice

Eligible Industries

Information and cultural industries
Professional, scientific and technical services

Funds Providers

Computer Research Institute of Montreal

Program status

Open

Overview

Get the support you need to realize your innovation project in digital, artificial intelligence, or information technology.

Activities funded

Data evaluation mandates and feasibility assessments for AI projects.
Development of experimental plans to address technological uncertainties.
Advancement of applied research aimed at practical applications.
Data preparation and consistency for machine learning processes.
Implementation of machine learning pipelines and unstructured data processing.
Development of time-series modeling and prediction methods.
Creation of recommendation systems and data visualisation techniques.
Audio and speech processing, including speaker and language recognition.
Vision and image processing for object segmentation and automated video indexing.
Natural language processing tasks such as sentiment analysis and chatbots development.
Geomatics and geospatial activities, like climate projections and biodiversity monitoring.
Cybersecurity initiatives, including internet of things security and user behavior analysis.
Application of formal methods in systems modeling and tests.

Examples of admissible projects:

$ 150,000

Creating a recommendation system for an e-commerce platform

$ 110,000

Developing a predictive modeling system for agricultural yield optimization

$ 150,000

Creating a machine learning model for fraud detection in financial transactions

$ 80,000

Developing a speech recognition system for customer service in a call center

$ 120,000

Implementing a machine learning pipeline to optimize logistics in a supply chain

$ 96,000

Developing a time-series model for predicting energy consumption

Eligibility

Eligibility criteria for this grant:

Applicants must be engaged in research or innovation projects.
Projects must involve AI or related technologies.
Applicants must demonstrate a clear plan for technology readiness and innovation.

Who is eligible?

The provided context does not contain specific information on evaluation and selection criteria for projects under this grant.

Who is not eligible

Some companies may not be eligible for this grant due to specific criteria. The following types may not be eligible:

Companies outside the specified industry sectors
Companies with fewer than a minimum number of employees
Companies that have previously received funding from certain sources

Eligible expenses

This grant supports projects focused on technological innovation and scientific research aimed at advancing applied methodologies and enhancing knowledge in various technological fields. Eligible activities span the development and application of AI technologies, data preparation, cybersecurity, and more.

Data preparation and machine learning pipeline development.
Signal processing and speech recognition techniques.
Object segmentation and automated video indexing.
Natural language processing for entity recognition and sentiment analysis.
Geospatial technology applications in climate projection and biodiversity monitoring.
Cybersecurity enhancements focusing on IoT and biometrics.
Formal methods for systems modeling and verification.

Selection criteria

There are evaluation and selection criteria for this grant. The criteria include:

Relevance to the funding program
Clarity and feasibility of the project
Potential impact and innovation of the proposed initiative
Quality and expertise of the team
Budget adequacy and justification

How to apply

Review the grant application guidelines

Prepare the required documents and information

Complete the application form

Submit the application before the deadline

Additional information

Here is additional relevant information for applicants working with CRIM:

CRIM provides access to experts who combine scientific and technical knowledge for applied innovations.
Knowledge transfer methodologies are included to ensure clients' autonomy post-project.
Stage-specific assistance from Technology Readiness Level (TRL) 2 to 6 is offered.
CRIM can support in various application areas, including machine learning and cybersecurity.

Documents and links

CRIM —Support

Apply to this program

Frequently Asked Questions about the CRIM —Support Program

Here are answers to the most common questions about the CRIM —Support. This section explains what the program is, how much funding is available, eligibility requirements, application deadlines, and other important details to help you determine if this grant is right for your business.

What is the CRIM —Support?

How much funding can be received?

What expenses are eligible under CRIM —Support?

This grant facilitates initiatives focusing on methodological advancements and technological innovation, enabling stakeholders to effectively navigate AI-driven projects and other technological undertakings. The eligible activities are designed to support various phases of project development. Data evaluation mandates and feasibility assessments for AI projects. Development of experimental plans to address technological uncertainties. Advancement of applied research aimed at practical applications. Data preparation and consistency for machine learning processes. Implementation of machine learning pipelines and unstructured data processing. Development of time-series modeling and prediction methods. Creation of recommendation systems and data visualisation techniques. Audio and speech processing, including speaker and language recognition. Vision and image processing for object segmentation and automated video indexing. Natural language processing tasks such as sentiment analysis and chatbots development. Geomatics and geospatial activities, like climate projections and biodiversity monitoring. Cybersecurity initiatives, including internet of things security and user behavior analysis. Application of formal methods in systems modeling and tests.