What is Shingo?
Shingo is a revenue-debugging system. It connects to your billing, analytics, error tracking, and product data — builds a causal behavioral model — and surfaces the specific bugs and behaviors costing you money. Then it ships engineer-ready fixes, ranked by dollar impact, directly to GitHub and Linear.
How it works
Most analytics tools show you what happened. Shingo tells you why — and what to do about it. Here's the pipeline:
Connect your stack
Plug in Stripe, PostHog, Segment, Sentry, and more. Shingo ingests billing events, user behavior, errors, and logs.
Build the causal model
Shingo maps user journeys to revenue outcomes and identifies causal links — not just correlations — between technical issues and money lost.
Get findings ranked by impact
Each finding includes the root cause, affected revenue, impacted users, and an engineer-ready fix with code context.
Ship to your workflow
Findings auto-create tickets in GitHub Issues or Linear, complete with priority labels and dollar-impact tags.
Key capabilities
Causation, not correlation
Goes beyond dashboards to find the actual technical cause of revenue changes.
Revenue-ranked findings
Every finding is tagged with the dollar amount at stake so teams fix what matters first.
Engineer-ready fixes
Each finding includes code context, affected files, and a suggested fix — not just an alert.
Workflow integration
Auto-creates tickets in GitHub and Linear with priority labels based on revenue impact.
Behavioral modeling
Maps user journeys end-to-end across billing, product usage, and error data.
Zero-config connectors
Pre-built integrations with Stripe, PostHog, Segment, Sentry, and more.
Who is Shingo for?
Shingo is built for engineering teams at companies where software quality directly impacts revenue. If your team spends time triaging customer complaints, debugging payment flows, or guessing which bugs to prioritize — Shingo replaces that guesswork with data.
- VP of Engineering / CTOs who need to connect eng work to business outcomes
- Product engineers debugging revenue-impacting bugs
- Revenue ops teams looking for technical root causes of churn
- Growth teams who want to know why conversion dropped — not just that it did
Next steps
Quickstart
Connect your first data source and see your first finding in under 10 minutes.
How It Works
Understand the causal model, the analysis pipeline, and how findings are generated.
Connectors
See which data sources Shingo supports and how to set them up.
API Reference
Programmatic access to findings, connectors, and the causal model.