Built for real studio workflows.
No code required.
See how game studios use Tsunagi to collect, transform, and route their data — from Steam reviews to LLM enrichment.
Real-time community monitoring for indie studios
The Problem
Your community team checks Steam reviews and Discord channels by hand. No single view. No trend detection. By the time you spot a problem, it's already on Reddit.
The Tsunagi Way
One blueprint pulls Steam reviews and Discord messages, runs sentiment and language detection, removes duplicates, and sinks to ClickHouse. Your Grafana dashboard updates in real time. Took an afternoon to set up.
Spin up a new data pipeline in 30 minutes
The Problem
You need to track player feedback for a new title. Your backend engineer estimates two weeks to wire up Steam, Discord, and Reddit APIs. Then another week for parsing, removing duplicates, and storage.
The Tsunagi Way
Write one YAML blueprint with your sources and sink. Deploy via Studio Desktop. Pipeline is live before your coffee gets cold.
AI enrichment without a separate ML stack
The Problem
Your data team wants sentiment scores and category tags on every review. That means spinning up a Python service, managing API keys, rate limits, retries, and fallback logic. Another system to babysit.
The Tsunagi Way
Add an llm processor to your blueprint. Pick Anthropic, OpenAI, or Ollama. Set a daily budget. If the API flakes, it falls back automatically. No new service. No new repo.
Fix a bug in production, replay without data loss
The Problem
You shipped a bad processor. For six days it mangled player events before anyone noticed. Your analytics are wrong, your reports are garbage, and you have no way to reprocess cleanly.
The Tsunagi Way
Rewind to the checkpoint before the bug. Fix your processor. Replay the exact event range. Bad events land in the failed events queue for inspection. Your data is clean again.
Test new pipeline logic on live data, safely
The Problem
You want to change how player events are categorized. But the only way to test is on production data, and if you're wrong, you pollute your warehouse. So you don't ship it.
The Tsunagi Way
Run your new logic in Shadow Mode. It reads live events, processes them with your new mapper, but writes nothing. Compare outputs side-by-side with production. Promote when the numbers look right.
Monitor schema changes and get alerted via Slack
The Problem
Steam adds a new field to their review API. Your pipeline keeps working but you don't know about the change until someone asks why the new data isn't in reports.
The Tsunagi Way
The schema_monitor processor detects the field addition, logs the change, and triggers a conditional sink that sends a Slack notification. Your team knows immediately.
Ready to own your pipeline?
Join the studios using Tsunagi to collect, enrich, and route their data — without writing code.
Get early access"Lovelace.gg processes millions of community messages daily across Discord, Reddit, and Steam using Tsunagi. When a connector fails, we trace the exact event, replay it, and fix the pipeline — without leaving our infrastructure."