A strong strategic advantage for many enterprises is their historical data. However, making this data "AI-Ready" is often a more significant undertaking than selected the model itself.
Internal data often lives in diverse formats across legacy systems. Without standardization, even the most powerful models struggle to extract accurate insights, leading to "hallucinations" where the model fills in the gaps.
The most successful AI initiatives begin with Data Hygiene. By investing in clean, validated schemas and robust ETL (Extract, Transform, Load) pipelines, you ensure that your AI is reasoning on ground truth. A standard model fed with excellent data will consistently outperform a custom model fed with noisy data.