Enabling GTM, Finance & CS to ship their own reporting, with Rig's context & automation tools
Birdiecare is a UK HealthTech building software for the domiciliary care industry. As the commercial org scaled, sales, customer success, and finance were all asking the same kind of questions (MRR by segment, churn risk, pipeline coverage, forecast) and each one routed back through a small data team. Birdie needed a self-serve layer that didn't compromise on governance.
From a small early-adopter group to the majority of the commercial org querying the warehouse directly inside Claude, in two months.
Same warehouse, four functions waiting on it.
Sales, finance, customer success, and marketing were all routing through the same data team. The questions were specific, recurring, and load-bearing for the business, and the bottleneck wasn't the warehouse, it was the queue in front of it.
Forecast, pipeline coverage, deal-by-deal context.
Every sales-leader pack needed a manual pull and a slide-build.
Monthly KPI pack, revenue forecasting, recurring-revenue reporting.
Numbers re-derived from scratch each cycle, no single shared view.
Retention deep-dives and account-level context for CSMs.
Account knowledge spread across the team, no shared live view.
Buying-stage intelligence, lead conversion, pipeline scorecards.
Reports often out of date by the time they shipped.
What Rig deployed
A managed context layer over Snowflake with certified metrics across sales, revenue and retention. Rig MCP rolled out across the commercial org so anyone could query from inside Claude. Workflow builder for sales, finance, CS and marketing to ship their own dashboards on the same context.
What Birdie has built on Rig
15+ dashboards and agents in active weekly use, owned by the function they serve. Grouped by theme.
Pipeline coverage, weekly forecast, deal-stage dashboards, end-of-period pipeline reviews.
Recurring-revenue by segment, monthly revenue reporting, forecast tracking against plan.
Buying-stage intelligence by cohort, funnel drill-downs, lead conversion analysis.
Retention deep-dives and customer-cohort trend monitoring for the CS team.
A rolled-up exec dashboard the leadership team checks daily.
The "Weekly Churn & Risk" app
By May 2026, the CS & RevOps team's churn work had gone from an idea to a live, recurring workflow, owned by the team and now one of their most routinely used workflows on Rig.
Define requirements for data engineers, then build Looker dashboards. A churn/usage rebuild two years ago took "a whole quarter".
CS & RevOps ask churn questions and ship recurring reports directly, over a context layer on Snowflake (MCP in Claude). The same rebuild was redone "in about half an hour".
An account-level churn and risk analysis, built with Rig's help to find where revenue is exposed before it's lost.
A self-serve report the team built themselves, now a standing part of Birdie's regular reporting cadence.
≈ 8 analysts' worth of work across Birdie's combined Rig workflow + MCP usage.
How the commercial team uses Rig MCP day to day
The shape of intents captured on actual Rig MCP calls, grouped by team and goal.
Recurring revenue by commercial segment, revenue for key accounts, monthly reconciliation runs.
Bookings forecast by quarter, won-deal detail, segment-level booking trends.
Customer cohort trends, retention monitoring, account-level enrichment for the CS team.
End-of-period cross-sell reviews, operational time-spent comparisons.