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Products
One flagship platform for governed data work, automation, ML, and AI execution.
Snaplytics is building around DataLAB, a platform that brings dataset management, SQL and SnapQL automation, machine learning, finance-heavy workflows, and governed AI-client execution into one product environment.
Flagship productDataLAB
DataLAB
A desktop-first data workbench with a server-ready workspace path
DataLAB is designed for finance teams, auditors, analysts, and data-heavy business units that need stronger workflows for managing, querying, transforming, validating, reconciling, modeling, automating, and analyzing business data.
- Lake-aware dataset management for files, folders, and connected data
- SQL and SnapQL automation for repeatable analytical workflows
- 40+ ML algorithms plus AutoML and experiment tracking
- Financial testing and reconciliation workflows
- AI-client execution through governed DataLAB tools
- Desktop-first delivery with a server-ready workspace path
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 and SnapQL 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.
AI-assisted finance and audit workflows
Run reconciliation, journal testing, anomaly review, and broader finance-heavy analytical workflows from the same product base, with AI clients able to execute approved actions.
How Teams Engage
Built for analysts, ready for AI-assisted teams
DataLAB is designed for serious analytical work while making stronger data, finance, model, and AI-assisted 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
The server-ready workspace path is designed for teams that want shared access, AI-client workflows, and future browser-based collaboration.
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.