Stop being a
screenshot service desk.
Define the query and the audience once. Chartcastr delivers every Pulse to every channel that asked, with AI commentary, anomaly call-outs and follow-ups in-thread. Your team gets back to actual analysis.
One materialised view feeds four different audiences. AI rewrites the commentary per channel: exec brief for #exec-weekly, ops tone for #growth-paid. No more “can you resend that for the leadership channel?”
Most of your week
isn’t analysis.
It’s six versions of the same Slack DM, landing every morning. Pull this for the standup. Resend the cohort chart. Same query, different ask. The work is mechanical; stakeholders just need the number where they already are.
The same query, on repeat
Schedule it once with Chartcastr. Every recurring DM becomes a Pulse that delivers itself, including the commentary.
You built the dashboard.
Nobody opens it.
Pull-based BI assumes stakeholders log in. They don’t. They wait for someone to walk them through it, or DM you for the screenshot. The dashboard isn’t the product; the delivery is.
Chartcastr is the missing last mile. Keep your warehouse, your modeling, your dashboards. Add a delivery layer that pushes what matters, to whoever needs it, on a cadence, with AI commentary so stakeholders can self-serve the “why”.
Three things that get
your time back.
One query. Many audiences.
Connect the source — BigQuery, Sheets, HubSpot, PostHog. Define the query. Route the same Pulse to as many Slack channels, emails or Teams groups as need it, filtered by owner, segment, or region.
AI commentary, not just charts.
Every Pulse arrives with a plain-English summary of what changed and why it matters. Stakeholders @mention Chartcastr in the thread to ask follow-ups. You stop being the lookup function.
Stop being the alarm clock.
Threshold breaches and unexpected movement get called out at the top of the next delivery — to the channel that owns it. The retention dip pings #cs before someone has to spot it in your dashboard.
Warehouse-friendly.
Spreadsheet-friendly.
Source-agnostic.
Pulses run off any source your team already trusts: BigQuery, Connected Sheets, OAuth connectors. No new ETL. No new modeling layer.
BigQuery
Run Pulses straight off your warehouse — Connected Sheets or native.
Google Sheets
The lingua franca. Anything an analyst already maintains becomes a Pulse.
PostHog
Product funnels, retention, feature adoption — pushed, not pulled.
HubSpot
Pipeline, MQL→SQL conversion, owner-level rollups.
Shopify
DTC revenue, cohort behaviour, refund deltas.
Xero
Cash, margin and AR signals into the finance channel.
Linear
Sprint velocity and incident counts for the eng leadership pulse.
A data team’s week, before and after.
- Half your week answering "can you pull X for Y?" Slack DMs.
- Dashboards you built that nobody opens — except to ask you about.
- Manual exports, screenshot, paste, paragraph of context. Every Monday.
- Stakeholders waiting on you to notice the anomaly before they hear about it.
- ✓Pulses run forever. Define source + audience once. Done.
- ✓Charts arrive where conversations already happen — with the answer attached.
- ✓AI writes the "what changed and why" paragraph for every delivery.
- ✓Thresholds fire on their own, into the channel that owns the metric.
Get out of the request queue. Back into the work.
Connect Google Sheets, pick a Slack channel, and get AI-powered metric updates with context your team can act on.
No card required. Setup in 3 minutes.
