Talent development, exploratory R&D projects, and recruitment
We’re laser-focused on doing the following things really well:
Develop AI talent supported by applied, real-world projects and practical mentorship.
Scale R&D projects, prototyping, and experimentation to highly capable teams with a minimum of cost, management, and onboarding.
Provide a turnkey solution for recruiting with significantly lower onboarding and workforce integration costs through customer specific AI R&D projects.
Don’t try to compete with tech giants for scraps of recognized AI talent
There’s a huge, untapped talent base out there searching for the opportunity to learn and deliver.
AI Launch Lab R&D Programs are designed to deliver high ratios of value to cost and time for partners while providing the training and mentorship that will help to create an AI ready workforce, expanding Montreal’s pool of AI talent.
AI R&D Project Mandates
AI Launch Lab R&D Programs offer companies the opportunity to mandate and scale R&D projects, prototyping, and experimentation to highly capable teams with a minimum of cost, management, and onboarding. All involved parties sign NDAs and all work and IP is owned by the project mandator. Our programs also provide solutions for recruiting with significantly lower onboarding and workforce integration costs through customer specific AI R&D projects.
AI Launch Lab R&D Projects comprise between 6 to 15 cohort members, typically with a background in CS or a related field. 50% are graduate students or attained a graduate degree and are working in industry, Others are experienced programmers or have other relevant knowledge and skills for a specific project. On average a team will work 150-200 hours per week on a project.
Project management and mentorship
Projects are managed by AI Launch Lab and mentors and experts are brought in to provide additional support and guidance for cohort members in order to limit human capital resource expenditures from mandators and to increase likelihood of best possible outcomes on project deliverables.
Since the beginning, the team has been present and met and even surpassed all our expectations. Their biggest asset is the way they choose the candidates. They literally spent tens of hours to read the CVs and application forms of the candidates, trying to detect who would be able to work with who and on what projects. This really makes a big difference. They will consider soft skills above knowledge and this proves to be a very efficient way to build up teams for such programs. We are doing fundamental research in AI with a team of non-experts, and it works!
Nikolaj Van Omme
AI R&D projects with
Interested in partnership, collaboration or in finding out more?