Just finished the 14-day trial. My goal was to see if it could fit into our existing revops stack for threat monitoring on sales tools.
Key takeaways:
* The query language is powerful but has a learning curve. Took me a few hours to get basic correlation rules working.
* Integration with cloud apps (like our CRM) seems limited to pre-built connectors. Couldn't find a way to pipe alert data directly into our internal dashboards without using the API.
* The automated investigation is fast, but the findings report is too technical for our sales ops team. Needs a summary layer.
Main question for users: How are you getting parsed alert data out and into other business systems (like a data warehouse or CRM)? Is the API the only real option?
The UI is clean, but I'm concerned about it becoming another silo.
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Yeah, the API thing is what I ran into as well. Their webhooks seem to only push to a few platforms like Slack out of the box.
For getting data into our warehouse, we ended up using a simple cron job to call their API and dump JSON into a staging table. It's extra work, but it beat having another silo for sure.
Has anyone tried using a tool like Zapier or Make as a middleman? I'm curious if that works with their alerts.
Interesting, hadn't considered using a cron job for that. Is the API rate limiting pretty forgiving?
I was also wondering about Zapier. Their API documentation mentions needing an API key and a sensor ID. Seems like you'd need to build the integration yourself in Zapier's UI, which might be as much work as your cron script.
You're right that building the Zapier integration can approach the complexity of a simple script. The real friction isn't just the sensor ID and API key - it's mapping their nested alert JSON to a flat structure that a tool like Zapier can reliably handle for each trigger. You end up building a parser either way.
On rate limiting - it's been forgiving in my experience, but that's not a guarantee. The bigger constraint for a cron job is usually the API's pagination logic when you're pulling historical data. You need to handle cursor-based pagination or date-windowing correctly to avoid missing alerts or hitting unexpected limits on large datasets. A naive `LIMIT 100` on each call will break.
Garbage in, garbage out.