SnowOptix started as a narrow tool for a Snowflake cost problem I understood directly. It identified meaningful savings on the bill that started the project, then got into the Snowflake Native App Accelerator with help from Snowflake’s startups team. That validation was useful. The category still looked weak as a company wedge: small market, improving native Snowflake observability, crowded alternatives, and adoption that stayed smaller and more episodic than the recurring contracts I wanted to build around. The valuable outcome was the set of conversations it created. Those conversations surfaced a different problem: B2B teams were spending heavily on events, while the handoffs across attendee lists, enrichment, outreach, booth activity, and CRM attribution were fragile. That opportunity became Luminik.
How SnowOptix started
At a previous role, the Snowflake bill kept growing. Queries were inefficient, warehouses were over-provisioned, and the data team was focused on shipping features before reducing costs. That happens often in fast-growing startups: speed comes first, efficiency gets attention once the bill is large enough.
Snowflake exposes plenty of metadata about query performance, warehouse utilization, and storage patterns. The data is scattered across multiple system views, and turning it into actionable insights requires real engineering effort. So I built a tool. The first version was simple: scripts that pulled the metadata, ran analysis, and generated recommendations like “this warehouse is idle 80% of the time, consider auto-suspend” or “these 10 queries account for 60% of your compute costs.”
Measured on the Snowflake bill that started the project.
SnowOptix entered Snowflake's Native App Accelerator with support from the startups team.
The category was competitive, increasingly served by native tooling, and weak for recurring contracts.
The conversations that changed the direction
My first intention was to understand whether SnowOptix could be a real product. The calls gave me a sharper answer. Snowflake costs were real. The commercial pull was uneven. Several conversations drifted toward GTM operations: how teams prepared for events, followed up, and explained ROI after the spend was gone.
I started asking for introductions. Those introductions gave me a second set of conversations with GTM leaders.
The pattern was consistent. Companies were spending heavily on events, and the operating process stayed manual across lists, enrichment, outreach, notes, and attribution.
SnowOptix vs Luminik: the decision to pivot
That left me with a choice. SnowOptix had real validation, including the Snowflake accelerator path. The business case still felt constrained. Snowflake’s own tooling was improving, the category was crowded, and the adoption I saw stayed smaller and more episodic than the contracts I wanted. Luminik had a clearer buyer, a larger budget surface, and a deadline that made the problem harder to ignore.
| SnowOptix | Luminik | |
|---|---|---|
| Market shape | Small category: Snowflake users with cost pain, many observability alternatives, improving native tooling. | Broader B2B pain across teams with sales targets and event budgets. |
| Buyer urgency | Useful pain with inconsistent budget pressure. Savings mattered, with priority often below other data-team work. | Marketing leaders had quarter-by-quarter pressure to defend event ROI. |
| Solution timing | Technically straightforward, increasingly served by platform-native observability. | LLMs made source, enrich, sequence, capture, and attribute more practical as one workflow. |
SnowOptix had validation. Luminik had a clearer buyer, larger budget surface, and stronger path to recurring contracts.
Why following curiosity beats following plans
I started with a problem I could feel in the work. The artifact changed the conversations I could have. Those conversations changed the market I understood. I trust that path more than a market map drawn before any customer has reacted to a product.
Side projects as discovery mechanisms
