<p>The bottleneck in building domain-specific AI has shifted from models to data. General-purpose models like GPT-4o and Claude Sonnet are widely available; the differentiator is high-quality, domain-specific training data. And increasingly, companies are generating that data synthetically — using AI to create AI training data.</p>
<h2>What Synthetic Data Means in Practice</h2>
<p>A bank wanting to fine-tune a model to classify loan applications according to its proprietary risk framework cannot use real customer applications (privacy and regulatory constraints). Instead, it generates thousands of synthetic loan applications — realistic but fictional — labeled according to its actual risk criteria. The model trained on this synthetic data learns the company's specific classification logic without any real customer data leaving the building.</p>
<p>A medical device company training a clinical documentation assistant generates synthetic patient notes that reflect the variety and ambiguity of real clinical language, without HIPAA concerns. A retailer wanting a demand forecasting model generates synthetic transaction histories that mirror seasonal patterns in their real data.</p>
<h2>Quality and the Feedback Loop</h2>
<p>The challenge with synthetic data is quality: if the synthetic data doesn't capture the complexity and edge cases of real data, the model trained on it fails in production. Companies are solving this with iterative pipelines: generate synthetic data, train model, test on real data, identify failure modes, generate more synthetic data targeting those failures, repeat. The loop converges when the model trained on synthetic data performs comparably to one trained on real data.</p>
<h2>The Market</h2>
<p>A synthetic data generation market has emerged around this need. Mostly AI (YC-backed), Gretel.ai, and Syntho are serving different segments — Mostly AI focuses on tabular financial data, Gretel on text and structured data, Syntho on healthcare. Enterprise licensing deals in the $100K-500K/year range are becoming common for companies with serious AI training programs.</p>