Is your data helping your GenAI solutions perform—or holding them back?
As GenAI systems mature, raw volume matters less than precision: redundant, noisy, or low-impact data can actively degrade model behavior and outcomes.
To win, your GenAI solutions need data that is deliberately evaluated, refined, and optimized for measurable performance gains.
The Challenge
When data optimization is overlooked, teams struggle with:
- Unclear performance impact: Teams can’t tell which data actually improves GenAI outcomes.
- Excess noise and redundancy: Low-value or duplicative data confuses models and retrieval layers.
- Unvalidated production readiness: Data changes are made without benchmarking or confidence in results.
Unoptimized data will cap GenAI performance, waste resources, and introduce unpredictable behavior in production.
Our Solution
In this hands-on workshop, your team systematically evaluates, refines, and validates data to maximize GenAI performance before production release.
- Evaluate data contributions to GenAI performance outcomes.
- Remove redundant or noisy data that degrades results.
- Prioritize high-impact records and signals.
- Benchmark the effects of data transformations on GenAI behavior.
- Lock optimized datasets for stable production use.
Area of Focus
- Evaluating Data for Performance Optimization
- Removing Redundancy and Noise
- Prioritizing High-Impact Records
- Benchmarking Data Transformation Outcomes
- Locking Optimized Data for Production Use
Participants Will
- Identify which data most improves GenAI performance.
- Eliminate data that adds noise or confusion.
- Focus investment on the highest-impact data assets.
- Quantify the effects of data optimization decisions.
- Deliver a production-ready, optimized dataset.
Who Should Attend:
Solution Essentials
Format
Virtual or in-person
Duration
4 hours
Skill Level
Intermediate
Tools
Evaluation frameworks, benchmarking datasets, and optimization workflows