SNADLY

Your data. A real database. In minutes, not weeks.

Connect your systems and get a clean, queryable foundation your team can inspect, extend, or deliver. Working the same day.

Product

The warehouse build, visible from end to end.

SNADLY turns raw source data into an inspectable warehouse, then gives teams the dashboards, lineage, reports, and relationship evidence they need to trust the output.

SNADLY dashboard showing an event locations map, generated charts, and data tables.
Generated dashboard Reports, maps, charts, and tables built from the new warehouse.
SNADLY Autopilot build screen showing warehouse build steps and progress.
Autopilot build One run profiles source data, infers relationships, designs the schema, and builds the warehouse.
SNADLY relationship inference screen showing source tables connected in a graph.
Relationship inference Inspect detected keys, dimensions, and table relationships before the project is built.

About the builders

Built by practitioners who have lived the data problem.

Adrian White

Adrian White

Auckland-based data, AI, and analytics practitioner.

Adrian White is an Auckland-based data, AI, and analytics practitioner with a track record of pioneering applied AI solutions. He has contributed to AI safety through red teaming work with Anthropic, was a top entrant in the inaugural HackaPrompt competition, and was one of the leading Snowflake contributors on Stack Overflow during the platform's rapid growth era.

Adrian demonstrated one of the world's earliest Snowflake AI integrations in Auckland in March 2023 and is the current world champion of PromptGolf. His work spans data platforms, AI evaluation, semantic search, accessibility technology, and rapid AI product development.

Corrin Lakeland

Corrin Lakeland

Builder of audited data systems, ETL pipelines, and applied ML products.

Corrin Lakeland builds systems that turn messy operational data into decisions a business can act on. He built his first neural network in 1993, completed a PhD in machine learning, and has been writing ETL pipelines since before "data engineering" was a job title, working across forecasting, warehousing, customer analytics, and automation.

He's also run his own businesses, using data inside them to sharpen pricing, marketing, and day-to-day operations. Being both the person who builds the pipeline and the person who depends on it taught him to treat analytics as engineering: output that's traceable, inspectable, and solid enough to trust.

Corrin has always built analytics to be audited and re-run, not just delivered. That's why he built SNADLY, to make that discipline something any team can rely on.

Portrait of Yadwinder "Yogi" Sharma

Yadwinder "Yogi" Sharma

Advisor — insurance and banking domain, and AI testing tooling.

Yadwinder "Yogi" Sharma advises SNADLY on the insurance and banking domains where much of the platform's work is concentrated. He brings more than nineteen years testing insurance, banking, and critical-infrastructure systems across New Zealand and globally, and has delivered over fifty testing programs for organisations including Suncorp (AA Insurance and Vero), IAG, Watercare, ACC, and Mercury Energy.

His insurance experience runs deep — spanning Guidewire claims implementations across multiple carrier brands, Salesforce platform delivery, and broker connectivity programs. Yogi is also the Founder and CEO of Nimbal, a New Zealand venture building AI-powered testing agents and quality-assurance tooling, selected into the MBIE-backed Ministry of Awesome accelerator and used by more than thirty customers worldwide. That combination of front-line insurance practice and AI-tooling discipline is what he brings to SNADLY as an advisor.

What SNADLY produces

The useful part before the dashboard.

Standard, inspectable output — not a black box. Every transformation documented — see where every number came from. Portable — hand it to anyone, use it anywhere. Working in minutes, not weeks.

Standard output

dbt SQL your team can inspect, modify, and keep using. No vendor lock-in.

Fast first value

Use your own data within hours instead of waiting through a long implementation cycle.

No black box

Every number is traceable to its source. The database is the product. The dashboard is optional.