Faster value from discovery to delivery
Whilst ML creates new possibilities for growth across industries, many organisations lack the expertise to leverage their data for ML or have the capacity to rapidly analyse the data to make informed decisions. With this relatively new discipline, some also may lack an enterprise-level maturity and strategy and focus more on proof-of-concept and experimentation levels.
Improve operations and efficiency by exploiting the hidden value of your data via AI, ML and MLOps (ML operations) with CGI AccelerateAI360—an open-source, cloud-agnostic, end-to-end ML engineering solution. Our service manages all aspects of the ML delivery lifecycle, giving your team the strategy, automation tools and microservices to support you in taking an ML solution into production.
Greater efficiency for smarter insights
CGI AccelerateAI360 is more than just an open and advanced MLOps platform. We combine the right technology for your needs with our deep industry expertise and delivery excellence to help you:
- Accelerate the realisation of value through modular ML architecture which speeds projects from prototype to production and reduces duplication of effort
- Make faster, more accurate predictions and better-informed decisions
- Empower non-specialists to automate ML capabilities
- Increase network throughput and reduce latency
- Increase data quality by reducing human error and the need for manual data entry
Our tried and tested process will help you develop automated systems that deliver genuine business value.
Work with our experts to review your current set-up and how we can help you advance along your automation journey.
Whether you are just starting your ML journey or have deployed systems, our solution will manage the whole delivery lifecycle with the automation tools you need to take a ML solution into production.
Modular ML architecture accelerating the realisation of value
Our modular ML architecture accelerates ML projects from prototype to production, delivering value faster and reducing duplication of effort across projects and initiatives.