Enabling Full-Stack GenAI Engineers
Making Your Product Data GenAI Ready Series
Certification Series
Is your product data ready to power reliable GenAI experiences?
Retrieval quality rises or falls on the data foundation. If your data isn’t structured, governed, and aligned to real use cases, GenAI behavior gets brittle fast.
To win, your GenAI solutions need GenAI-ready product data that reliably supp
The Challenge
Without a strong approach to GenAI data readiness, teams struggle to:
- Define what “GenAI ready” means across teams, products, and data domains.
- Fix messy, fragmented, inconsistently formatted data that breaks retrieval and response quality.
- Validate governance, privacy, and compliance risks before they become production issues.
Our Solution
In this hands-on series, your team defines GenAI-ready requirements, assesses gaps, and builds a practical readiness plan using structured exercises and realistic product data scenarios. The series culminates in an applied capstone with expert coaching where your team will build a readiness framework.
Area of Focus
- Defining GenAI Ready Requirements — Set clear standards for structure, quality, and usability.
- Gap and Risk Assessment — Identify weaknesses that undermine retrieval quality and trust.
- Context and Format Design — Align data shape to how GenAI systems retrieve and rank information.
- Ethical and Legal Compliance — Anticipate constraints around privacy, rights, and responsible use.
Skills You'll Gain
- GenAI Data Readiness Standards — Define measurable criteria teams can align on.
- Retrieval-Driven Data Design — Shape data for higher-quality context selection and ranking.
- Risk and Compliance Planning — Spot governance issues early and reduce downstream surprises.
- Faster Iteration Cycles — Reduce rework by fixing data constraints before model and app tuning.
- Production Readiness Playbooks — Create repeatable patterns your teams can apply across use cases.