Lean AI SDLC: how CI&T is reinventing agility in Ways of Working Jun 17, 2026 A man wearing glasses intently watching a computer screen. Learn more
What your AI deployment partner should be telling you. And what it means if they’re not. Jun 24, 2026 That gap is the whole game. It is where transformation happens, or doesn’t. And it is the part that can’t be bought off the shelf, because it lives inside your people, your data, and your processes. So the question is not which model you bought, it’s whether the people building your harness are telling you the truth about what it takes to make a deployment successful. Learn more
Volkswagen of America Selects CI&T as Digital Agency of Record Jul 20, 2025 CI&T is a global technology transformation specialist, has been named the Digital Agency of Record (DAOR) for Volkswagen of America, Inc. Learn more
Increasing DEV Power with Augmented Coding Oct 28, 2022 Technological approaches and resources accelerate tasks associated with software development and maintain the quality of actions. This is Augmented Coding. Learn more
Solving CPG and Retailer Demand Forecasting Dilemmas Download The retailer-supplier relationship isn’t arranged in the way most conducive to confident demand forecasting. In this new report CI&T examines the demand forecasting relationship between retailers and suppliers. The report highlights pain points and opportunities for both parties, revealing a misalignment of data strategies causing ineffective forecasting. DOWNLOAD THE FULL REPORT Key findings from the report include: Suppliers’ highest ranking challenge related to forecasting demand was visibility and access to data. Retailers’ highest ranking challenge related to demand forecasting was scaling the data platformSuppliers reported they were most likely to break demand forecasting down by geography, while retailers were most likely to report breaking down demand forecasting by channel The majority of suppliers reported looking at sales data from the same month over years prior as their predictive approach, while the majority of retailers reported referencing the previous month’s sales to predict the following monthBoth suppliers and retailers overwhelmingly reported that consumer-level data (gender, age, household size) is the most likely type of data leveraged for demand forecasting