Building an AI Platform for 50M Events/Day
How we designed and engineered HeliosAI's real-time analytics platform from zero — and what we learned along the way.
Building an AI Platform for 50M Events/Day
HeliosAI is a Series B startup building AI-powered product analytics for companies that have outgrown off-the-shelf tools. They had a validated concept and strong traction — what they lacked was a production-grade data platform.
Analytics platforms must handle enterprise-scale data from day one. HeliosAI needed sub-5ms query latency on billion-row datasets, real-time processing with no data loss, and AI insights that were accurate rather than confident-sounding hallucinations.
Three weeks of discovery mapped the query patterns of their target customers. We settled on Kafka → ClickHouse with an intelligent query-planning layer, and an AI engine that generates an internal query language instead of raw SQL — giving us full control over what the model could do.
The platform shipped in 18 weeks: SDK/API ingestion, real-time stream processing, pre-aggregation, on-demand queries, and a natural-language insight chat. The dashboard went through four rounds of user testing.
Time-to-insight dropped from 12 minutes to under 90 seconds. The platform now runs at 10x its launch load without architectural changes.
We hired three agencies before finding BuddyDevs. The difference was immediate and obvious — they actually understood what we were building and had strong, specific opinions about how to build it better. The architecture they designed is still holding up under 10x the load we launched with.
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