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Products
One flagship platform, designed for serious data work.
Snaplytics is building around DataLAB, a platform that brings SQL analytics, data operations, machine learning, and finance-heavy workflows into one product environment.
Flagship productDataLAB
DataLAB
A desktop-first analytics platform with an early web MVP
DataLAB is designed for finance teams, auditors, analysts, and data-heavy business units that need stronger workflows for querying, transforming, validating, reconciling, and analyzing business data.
- SQL analytics for practical business workflows
- 40+ ML algorithms plus AutoML and experiment tracking
- Dataset management with metadata, contexts, and persistence
- Financial testing and reconciliation workflows
- Pipeline and automation support for repeatable data work
- Desktop-first delivery with an early web MVP
Current Focus
What DataLAB already covers
The strongest way to present the platform is by the real categories of work it already supports.
Analytics and data operations
Use SQL to inspect, transform, validate, and export data while keeping datasets organized through metadata-aware workflows.
Machine learning workflows
Train, compare, track, and evaluate models in the same environment rather than handing work off to a separate specialist stack.
Finance and audit analysis
Run reconciliation, journal testing, anomaly review, and broader finance-heavy analytical workflows from the same product base.
How Teams Engage
Built for analysts, aimed at bringing advanced analytical tools to everyone
DataLAB is designed for serious analytical work while making stronger data, finance, and model workflows more accessible across the wider team.
Desktop
The deepest product surface today. Best for power users and teams that want the full working environment already available in DataLAB.
Web
DataLAB web is an early browser-based MVP that exists for evaluation and learning, but is not yet the main client-facing product surface.
Pilot engagement
The current commercial motion is centered on demos, design-partner conversations, and focused pilot validation around real workflows.
Ready to see DataLAB in action?
The best next step is a walkthrough tied to your actual workflow, whether that is analytics, data preparation, ML, or finance review.