
We can run it ourselves. Aleph connects natively to Snowflake, Salesforce, Rippling and our GL (Rillet), and we manage our own tables, dimensions and mappings. We launch new products most quarters, so that matters a lot. We came from Cube, where every new dimension or business line meant going back to them to rebuild the data pipeline. Setup with Aleph took a couple of days.
The day-to-day stuff is well thought out. When accounting adds new GL accounts I get a Slack message with AI-suggested mappings, and I usually just click accept right in Slack.
The AI features are also very useful. The variance explanations give us a good first pass and knock out the easy ones, and we pull Aleph data into Claude through their MCP for ad hoc analysis.
Support is the other big one. We have a shared Slack channel with their team and they're super responsive. The roadmap moves fast, and when I ask about something it's often already slated for an upcoming sprint. Review collected by and hosted on G2.com.
Not much. The main thing is that you get out of it what you put in. You can set it up the lazy way, with auto-refreshing tables you look up into, or you can design your tables and model so the whole thing is a true one-click refresh. The second takes more thought up front and pays off every month after. If you're starting out, spend real time on table design before you build. Review collected by and hosted on G2.com.