Answering your last question first:
> Do you replace a big league $150k stack of fancy vendors
Yes, exactly.
You get full and scheduled incremental ETL from source systems, a data lake, an integrated agent, a data modeling layer that the agent can write to and read from, visualization tools (simple charts) and the ability to share your models with colleagues, agents, and BI tools.
Also IMHO your $150k estimate is low and does not factor the personnel cost to deploy and maintain; a seasoned data engineer is >$150k.
> A semantic / ontological layer you just do that for me after I click connect?
We can automatically profile and add context to your data, but the most powerful modeling comes from you giving instructions, just like you would to a business analyst or analytics engineer.
E.g. "Analyze the potential and actual ROI on paid advertising over the past 12 months."
Based on the systems you’ve connected (e.g. Google Ads, Salesforce, etc.) we create a model that gets the spend, the pipeline and revenue generated from ads, inferring pipeline attributable to ads (e.g. lead source or a multi-touch model)
If certain tables or columns are missing from our sync process, we seek approval to add them.
Then you can save this model and make it accessible everywhere - to your colleagues, the Datachef agent, to Claude, to your visualization tools (e.g. Tableau Desktop - Free Edition) wherever you need it. This part replaces dbt.
I’d love to get your feedback on our product, we offer a free trial but mention Hackernews and I’ll extend that to as long as you need to thoroughly vet: https://www.datachef.com