Analytics for indie games (loopkit.ai). Built, then shut down not long after.
The idea came from my own game. I used analytics to rework its tutorial and got 70% more players past the 15-minute mark. When I talked to other indie devs about it, most had never run an experiment like that. Not because they couldn’t, but because nobody in a small team has the time to set up a data pipeline, build charts, and learn to read them. Big studios have telemetry teams for this. Indie devs have themselves.
LoopKit was meant to close that gap: send events from your game, and instead of a dashboard you have to interpret, agents watch the stream and tell you what changed, what’s broken, and what to try. The bet was that AI tools are letting more people ship games faster, often with less engineering background, and those people need the analyst included.
The stack:
- Event ingest: over Kinesis, processed as events arrive rather than in batches.
- MotherDuck: the analytical warehouse.
- Agents: doing the interpretation, context assembly, and alerting.
- SDKs: for Unity, JavaScript, and React.
- Serverless on AWS: idle cost was near zero.
It died on market fit. Indie devs mostly treat their games as art, not as a min/max data problem, and pitching AI-driven telemetry to that audience landed badly on both counts. I think we were early rather than wrong. The same shift that’s lowering the barrier to making games is producing developers who need this, so it may come back.