DOWNLOAD NOW

GUIDE

Scaling GenAI without breaking ROI

Scale GenAI with confidence – without blowing your budget or trust. Learn how Cloud and FinOps teams turn experimentation into measurable ROI with practical advice from DoiT AI and Machine Learning specialists Eduardo Mota and Rupal Bhatt. 

What you’ll learn

  • How to identify GenAI use cases that actually deliver business value

  • Best practices to balance quality, latency, and cost in real-world, probabilistic AI systems

  • How to move from GenAI pilot to production using cohort-based scaling in “waves”

DOWNLOAD NOW

A look at what's inside

How to Balance GenAI Performance

GenAI systems force engineering teams and business leaders to manage trade-offs, not chase perfection. Pushing for higher accuracy drives up compute costs, while ultra-low latency can degrade quality - real ROI comes from finding the balance that users notice and the businesses can reasonably sustain.

“Finding the balance where quality hits the right level, latency stays reliable, and cost stays manageable. That’s how you protect ROI.”

- Eduardo Mota, guide author, DoiT Senior Cloud Data Architect

More GenAI ROI best practices inside

Why starting with internal, employee-facing GenAI reduces risk and accelerates real-world learning before customer exposure
How to define unit economics for GenAI (time saved, cost per outcome) before writing code

Where GenAI projects fail most frequently – and how defining clear success and failure paramters prevents stalled pilots

Why data retrieval, not model choice, becomes the primary bottleneck at scale
How persona-aware design (junior vs. senior users, async vs. real-time) directly impacts adoption and ROI

Learn how modern FinOps teams are turning AI cost chaos into clarity across AWS, GCP, and beyond

DOWNLOAD NOW

Schedule a call with our team

You will receive a calendar invite to the email address provided below for a 15-minute call with one of our team members to discuss your needs.

You will be presented with date and time options on the next step