BI for the 90% of Teams Who Don't Have a Data Warehouse
Most companies aren't Snowflake shops. Their data lives in Sheets, Shopify, HubSpot, and ad platforms. Here's why Chartcastr is built for them, not the other 10%.
BI for the 90% of Teams Who Don't Have a Data Warehouse
If you read analytics Twitter, you'd think every company has a Snowflake account, a dbt project, and a semantic layer. They don't. Most teams we talk to don't have a data warehouse. They have a Shopify store, a few ad accounts, a HubSpot CRM, and a Google Sheet someone in ops has been maintaining for three years.
That's the 90%. It's who we built Chartcastr for.
The industry keeps shipping tools for the 10%
A new wave of AI-native analytics tools is arriving, and most of them share the same assumption: you already have a warehouse. They wire AI analysts into Slack that write validated SQL against Snowflake, BigQuery, Postgres, or Databricks. Hex, Mode, and Equals all assume a warehouse at the other end of the pipe.
These are good products. If you have a data team and a warehouse, they'll make you faster. But they also reveal something about where the category is pointed: Slack is the new BI surface. Instead of a dashboard that nobody opens, insight lands in the channel where decisions actually get made.
We agree with the thesis. We disagree about who's at the other end of the pipe.
Most teams don't have, or need, a warehouse
Warehouses solve a specific problem: unifying data across many sources at a scale where spreadsheets break. If you're a 20-person agency, a growing Shopify brand, or a startup pre-Series B, you probably don't have that problem yet. You have:
- Revenue in Shopify or Stripe
- Spend in Google Ads, Meta Ads, LinkedIn Ads
- Customers in HubSpot or Salesforce
- A Google Sheet that someone built to track the weird KPI your CEO cares about
- Maybe BigQuery, if a consultant set it up and nobody has touched it since
Forcing that shape of data into a warehouse is an expensive, slow project with no guarantee the output ever gets used. Most SMBs can't afford it, and honestly, most don't need it. What they need is the weekly number, in Slack, on Monday morning, with a sentence explaining what changed.
That's the product
Chartcastr connects directly to where the data already is: Google Sheets, Shopify, Google Ads, Meta Ads, HubSpot, Xero, Notion, BigQuery if you want it. You pick a metric, pick a schedule, pick a Slack channel. A chart and an AI summary land there automatically. If someone has a question, they reply in the thread and the AI answers, grounded in the same data.
No warehouse. No SQL. No dashboard that nobody opens. No analyst screenshotting charts into Slack at 9am on Monday.
Same thesis, different wedge
The query-first AI analyst tools, the dashboard-first BI tools (Looker, Tableau, Sigma), and the spreadsheet-native ones (Equals, Rows) are all working toward the same future we are: insight delivered to the tools people already use, written in language they already understand. We're just starting from a different place.
They start with a warehouse and a data team. We start with a Google Sheet and a Slack workspace. Both roads lead somewhere useful. Ours leads to the 90% of teams nobody else is serving yet.
If you have a warehouse and a data team
Honestly? Go use Hex or Mode. They're built for you. If you don't, or if you have a warehouse but your ops, marketing, and founders still live in Sheets and Slack, that's us.
Connect your first source and get a pulse into your Slack in under three minutes.