How HeyMax scaled trusted analytics with Sundial
Everyone had data. No one had the same answer.
As HeyMax grew, so did its tool sprawl. Product ran experiments in Statsig. Finance and Operations lived in Superset, Looker Studio, and Google Sheets. Canonical tables existed, but with no shared semantic layer, one question could return three different answers depending on who asked it.
Analytics stopped accelerating decisions and started gating them. Every request meant re-validating definitions, reconciling dashboards, and re-answering questions the team had already settled.
HeyMax didn't need another BI tool. It needed one trusted foundation, one that could keep pace with the company's growth.
One semantic layer. One source of truth.
Sundial built a shared semantic layer directly on top of HeyMax's warehouse: a single place where metrics, business logic, and source tables are defined once and reused everywhere.
Work that would have normally taken weeks, Sundial's data modeling agent one-shot it.
The shift changed the data team as much as it changed the analytics. Instead of writing transformations, maintaining dashboards, and adjudicating metric disputes, they went back to expanding what the business could actually analyze.
On that foundation, Sundial's AI analytics agent lets anyone ask a question in plain language, with every answer grounded in those trusted definitions.
"Using Sundial is like getting an AI data organization working for us. We're able to do more with much less, taking away a lot of the tedious work and allowing us to get to insights much faster and confidently."
Results: from bottleneck to company-wide self-service
Adoption across the company. More than half of HeyMax uses Sundial regularly to answer questions with trusted analytics.
One tool instead of five. Product, Marketing, Operations, Engineering, and Finance have consolidated onto Sundial. Same definitions, same numbers, nothing left to reconcile.
Answers in minutes, not queues. Questions go in as plain language. Analyses that once took days now close in minutes, and business users trust what comes back.
Data modeling on autopilot. Sundial runs the end-to-end workflow: writing transformation logic, opening pull requests, running backfills, validating changes. New metrics and models reach users in a fraction of the time.
Growth without growing the data team. As the business expanded, HeyMax scaled it without scaling headcount, freeing data engineers for higher-leverage work instead of routine maintenance.
Trust built into every analysis. Repeatable playbooks and data best practices are embedded in each workflow, with trust signals tied back to the semantic layer. A self-serve analysis holds to the same standard as one from the data team.
A semantic layer that compounds. Every new question surfaces gaps in coverage and helps extend the layer, turning everyday usage into continuous improvement.
"Sundial is like having a business analyst on demand. It knows our data and our context, follows the playbooks our team has set up, and lets me self-serve everything from retention analysis to campaign tracking without waiting in the data team's queue."
Most companies scale analytics by adding dashboards, tools, and headcount. HeyMax did it by giving the whole business one shared understanding of its data.
Half the company now answers its own questions. The data team never had to grow to make that possible. And work that used to run in weeks (a new model, a new metric, a full analysis) now lands in hours or minutes. With Sundial holding the foundation, HeyMax is compounding faster than a data team its size could carry alone.