From Data to Intelligence: Unlocking the Power of Amazon SageMaker
For many teams, data feels more like a burden than a competitive edge. Hours go into collecting, cleaning, and experimenting, only to hit the same wall: how do we turn all this information into something that works and delivers real value?
It’s a common story, a familiar change Business leaders want AI to drive outcomes but get stuck between ready-made solutions or building something custom, tailored to their needs. Meanwhile, tech teams juggle complex deployments, slow experiments and mounting pressure to optimize costs.
This is where Amazon SageMaker steps in.
Why SageMaker Matters
Think of it as a single workspace where your team can:
- prepare data,
- train custom AI models,
- deploy them into production, and
- keep them running reliably—without reinventing the wheel every time.
No need to rebuild or stitch together tools every time. Amazon SageMaker connects raw data to business-ready AI systems in one place.
And the best part? It doesn’t just simplify workflows. With proven optimization techniques, SageMaker can help organizations cut AI-related costs by as much as 70–90%.
The Human Side of AI
Behind every AI project is a team trying to move faster without losing control:
- the IT manager who needs reliable output,
- the engineer who stays up late chasing bugs instead of results
the leader who dreams of innovating faster, trying to scale without runaway spend Our webinar was built for them. Less theory, more actions. It’s more than just technology; it’s about making AI approachable, practical and sustainable for real teams and real businesses.
The session is led by two seasoned professionals who understand both the promise and the pain of bringing AI into production:
👨💻 Hubert Puacz – Cloud Solutions Architect
An expert in designing scalable cloud architectures, Hubert helps businesses harness AWS to unlock the true potential of AI.
⚙️ Krystian Kozieł – MLOps Engineer & Technical Leader
A specialist in CI/CD for ML, observability, and governance, Krystian guides teams in transforming experimental models into secure, reliable deployments.
Together, they’ll walk you through the full AI lifecycle with SageMaker, showing you how to balance innovation, governance, and cost efficiency.
Join us and discover how to make Amazon SageMaker work in the real world, balancing innovation, governance, and speed.
Don’t let your data remain untapped potential!
