Generate your first dataset from a template
A five-step walkthrough with screenshots: pick a prebuilt industry schema, review the plan, generate straight to S3, and read the scored quality report.
Read the guide →The dataset that started as one sentence
No template fit, and writing DDL for a throwaway fixture felt like a bad trade. So he described it in a sentence and let CrossRow draft the plan.
Read the guide →What “production-grade” synthetic data actually means
Realistic-looking values are easy. Data whose ledgers reconcile, foreign keys resolve, and state machines walk legal paths is a different problem. Here is the bar, with worked examples.
Read the guide →Why random fake data breaks your integration tests
Faker gives you well-formatted nonsense. The moment your tests assert anything about relationships between rows, that nonsense starts failing in ways that look like your code’s fault.
Read the guide →The demo that kept falling apart
An engineer builds a demo dataset the quick way and watches it break one invariant at a time. Each failure is a lesson in the rules that only live across rows.
Read the guide →How CrossRow scores its own output
Every run ends with an independent verification pass and two scores. Here is what Structure and Realism measure, and why a generator that grades itself is one you can put in front of an auditor.
Read the guide →Synthetic data for fine-tuning: teaching models the right patterns
Text-to-SQL, structured extraction, and tabular training. Three fine-tuning use cases, and which capabilities keep a model learning real relationships instead of a generator’s artifacts.
Read the guide →The fraud model that aced the test and failed in production
A detector scores 0.98 in validation, then misses real fraud. The training anomalies had the wrong shape. Why real anomalies cluster, and how to generate them that way.
Read the guide →When your churn model thinks everyone is leaving
Train on a balanced synthetic set and you ship a model that cries churn at every customer. How to generate the imbalance you actually face, with exact labels.
Read the guide →The text-to-SQL model that wrote perfect queries against nonsense
The SQL parsed and executed. The answers were still wrong, because the database underneath did not hold together. The substrate that fixes it.
Read the guide →The wallet demo that wouldn’t balance
A finance reviewer catches that the ledger doesn’t foot. The rebuild takes one plain-English sentence. A workflow for chained-balance data that reconciles.
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