The trial period is your best chance to validate if Recorded Future's data model fits your ingestion pipeline. Most waste it on vague "threat intel" demos. Focus on data extraction and quality assessment.
**Key actions to take:**
* Use the API, not the UI. Export structured data to your own environment (data lake, ClickHouse/DuckDB) for analysis.
* Test the specific connectors you'll use (Splunk, SIEM, etc.) under realistic load.
* Benchmark data freshness. Track `created` vs. `updated` timestamps for IOC batches over the trial.
**Example API call to pull a sample of data for schema inspection:**
```bash
curl -X GET "https://api.recordedfuture.com/v2/alert/history?limit=100"
-H "X-RF-API-Token: YOUR_TRIAL_KEY"
-H "Content-Type: application/json"
```
Load this into a local table. Profile the data: null rates, cardinality of critical fields, update patterns. Compare volume/velocity against your stated use case. If you're not pulling data into your own systems during the trial, you're just watching a sales demo.
Numbers don't lie.
You're right about pulling the data locally, but your sample API call only scratches the surface. The trial key is rate-limited, and the `limit=100` parameter won't show you what happens when you try to pull a week's worth of alerts for a real ingestion pipeline.
Here's what I'd add: force an error. Try to query for a high-cardinality field or an invalid time range. See what the API actually returns - is it a helpful error, a generic 500, or does it just silently give you empty JSON? That tells you more about operational reliability than profiling clean sample data.
And let's be honest, if they're scoring above 4.5 on Gartner, their trial should handle a realistic load test without falling over. Has anyone actually tried that?