https://store-images.s-microsoft.com/image/apps.19182.ee253b94-dfcd-4e04-9d65-97041b971eec.1a16e125-b376-4c34-b790-8384ca1e2242.e253e5f7-93ac-46a3-87fd-ccb6b995ea60

Generative AI Factory & GenAIOps ((AI Transformation Offer Component 3)

CGI Inc.

Component 3 of CGI’s AI Transformation Offer industrialises AI delivery through a Generative AI Factory and GenAIOps, enabling repeatable, governed, and scalable deployment of AI solutions at pace.

Generative AI Factory & GenAIOps (ATO Component 3)

These offers are the modular components of the Microsoft AI Transformation Offer (ATO) a structured, end-to-end approach to moving from AI ideas to production at scale. Each component is designed to stand on its own (so you can start where you are), or to be combined into a single, sequenced program: (1) Strategy & governance → (2) Technical foundation → (3) Industrialised delivery and operations. CGI can deliver any one component independently, or orchestrate all three as a comprehensive transformation.

Typical outcomes

  • Faster, safer release cycles for generative AI solutions
  • Consistent governance and measurable quality through evaluation and monitoring
  • A scalable delivery model that supports multiple teams and use cases

What this component delivers

Component 3 turns AI from isolated initiatives into a continuous, scalable capability. CGI establishes a Generative AI Factory and embeds GenAIOps practices so solutions can move from idea to production quickly and reliably, including:

  • GenAIOps maturity assessment and target operating model
  • Standardised processes for developing, evaluating, deploying and updating AI solutions
  • Monitoring, governance and continuous improvement loops (quality, risk, cost and performance)
  • Reusable delivery patterns to enable repeatable, industrialised AI delivery across multiple use cases

Why choose CGI

  • Microsoft-aligned delivery: Collaboration with Microsoft specialists and accelerators to increase delivery speed and confidence. Eligible engagements may receive Microsoft post-sales funding.
  • Industrialised delivery: Factory approach creates repeatable patterns so multiple use cases can scale without reinventing ways of working.
  • Operational rigour: Monitoring, evaluation and governance loops help maintain quality, safety and cost control in production.
  • Built to integrate: Designed to work with your CoE governance and Azure foundations, reducing friction across teams.

How it connects to the other ATO components

Use Component 3 when you want to operationalise and scale delivery across many use cases. It is strongest when:

  • Informed by Component 1 so the Factory aligns to CoE governance, priorities and guardrails
  • Built on Component 2 so deployments run on a secure Azure AI Landing Zone with enterprise baselines

Related AI Transformation Offers:

  • AI CoE and Solution Envisioning (Strategy & Governance)
  • Azure AI Foundation Architecture (Landing Zone Implementation)

Microsoft partnership and funding

Microsoft will participate alongside CGI with cloud architects, engineering specialists and solution experts (including Cloud Accelerate Factories) to support delivery and customer success. In some cases, Microsoft funding may be available for eligible engagements, subject to Microsoft criteria and approval.

Delivery model

Workshops + 6–8‑week PoV + AI Factory integration.

Pricing

Scope‑based; Microsoft post‑sales funding may apply.

At a glance

https://store-images.s-microsoft.com/image/apps.24352.ee253b94-dfcd-4e04-9d65-97041b971eec.1a16e125-b376-4c34-b790-8384ca1e2242.993d89ec-117d-4c02-b122-89c7ff5ca058
https://store-images.s-microsoft.com/image/apps.46329.ee253b94-dfcd-4e04-9d65-97041b971eec.1a16e125-b376-4c34-b790-8384ca1e2242.28d18e7a-1c7d-481c-9b16-b2128c417fbb
https://store-images.s-microsoft.com/image/apps.46191.ee253b94-dfcd-4e04-9d65-97041b971eec.1a16e125-b376-4c34-b790-8384ca1e2242.a4b944e9-038f-41fb-a3e2-adba3a6962da
https://store-images.s-microsoft.com/image/apps.58470.ee253b94-dfcd-4e04-9d65-97041b971eec.1a16e125-b376-4c34-b790-8384ca1e2242.b43be6c7-70e3-4409-b901-5796187cb8fc