Explore
Review examples before you ask for access.
Open the completed AutoML run, the Reproducible Analytics Studio example, and the docs to see the kind of outputs each product keeps visible.
Products, access, and pricing
Compare the two main products, inspect the proof, and decide whether to request access for your workflow.
Company overview
Access by request
Examples before access
Compare products
Start with the work you need to do.
If you already know the work you need to do, this table should get you to the right product route quickly.
| Product | Best fit | Access status | Access and pricing | Next step |
|---|---|---|---|---|
| Xalec AutoML Services Machine-learning workflows |
Supported data uploads, readiness checks, model training, model comparison, SHAP explanations, model review, saved artifacts, and reports. | AutoML workspace access is currently by request. | Subscription allowance plus credits is the intended model; detailed checkout and usage estimates will live in the AutoML platform. | View AutoML overview → Discuss AutoML access → |
| Reproducible Analytics Studio Statistical workflows |
Data dictionaries, EDA, statistical tables, prevalence outputs, predictor outputs, figures, method notes, and manuscript-oriented reports. | RAS workspace access is currently by request. | Early access and final tiers will be listed on the dedicated product platform when workspace rules are ready. | View product overview → Discuss RAS access → |
Access and pricing
Use these access paths to decide your next step.
Exact checkout and usage estimates live in the product workspaces. For now, use these paths to evaluate fit before you contact anyone.
Pilot or early access
Start with a scoped workflow.
For near-term use, share the product, dataset type, workflow, expected outputs, and timeline. That makes it easier to confirm whether a pilot or early-access path is realistic.
Request access →Organization
Discuss security, data handling, and support early.
For team or institution use, the right conversation includes privacy, retention, secure transfer, support expectations, and whether a dedicated setup is needed.
Review security basics →Product workspaces
Live work happens in each product workspace.
This company site helps you compare products. AutoML and Reproducible Analytics Studio keep live uploads, saved jobs, pricing details, and support inside their own workspaces.
Trust and security
Review the basics before sharing data.
Review security, privacy, responsible disclosure, and legal basics before sharing data. Product-specific data handling should be confirmed in the relevant product workflow before live customer data is used.
Access or fit discussion
Tell us what you want to run.
A useful first note includes the product, dataset type, workflow you want to improve, whether the work is individual or team-based, and any security or timeline constraints. If your work sits outside AutoML or Reproducible Analytics Studio, we can discuss whether it should be scoped separately.