From uploaded data to results people can understand and review.
Xalec AutoML Services is the flagship product experience from Xalec AI. It turns raw data into understandable, reviewable results through guided uploads, data checks, model comparison, prediction explanations, reporting, and prediction in one connected application.
Too many analytics teams still bounce between notebooks, scripts, dashboards, and slides. AutoML Services brings the workflow together so modeling outputs can be reviewed, trusted, and acted on responsibly.
The workflow is usually harder than the model.
Many teams can get a model to run. The harder part is choosing the right workflow, validating the data shape, tracking progress, understanding cost, producing explainable outputs, and turning technical results into something reviewable by stakeholders. AutoML Services is designed around that full workflow rather than only the training step.
How users move from raw data to decision-ready outputs.
The app is designed to keep your work connected instead of making you restart on each page.
Guided service selection
Start by data shape and objective instead of forcing every problem into the same upload form.
Upload and readiness review
Preview the required columns, role assignment, warnings, and recommended models before spending credits.
Curated multi-model evaluation
Train candidate models, compare them on the right metrics, and keep progress visible in the workspace and job page.
Explainability, reports, and prediction
Use saved job outputs for SHAP, AI reporting, exports, and prediction.
Evaluation before hype.
Built for harder workflows
The strongest differentiator in the product today is that more complex structured workflows are treated as first-class: longitudinal and repeated-measures analysis, survival, count modeling, ranking, recommendation, and report-heavy work.
One consistent shell
The homepage, services catalog, upload pages, workspace, job detail view, reports, prediction flows, and billing cues are meant to feel like one guided product rather than disconnected tools.
Trust through saved evidence
Saved outputs, validation notes, references, figures, and matching exports matter because trustworthy analytics should be reviewable after the job completes, not only while the page is open.
Teams that need workflow ROI, not just model novelty.
AutoML Services is useful for analysts, researchers, public health teams, clinical and outcomes researchers, evaluation teams, and technical operators who need a workflow that is easier to use than a custom ML stack but more transparent than a one-click black box.
It is especially strong when the work is messy, governed, report-heavy, or structurally more complex than a standard tabular prediction problem.
See the product in action from the route that fits your goal.
Explore the services catalog if you are starting a new analysis, or open the workspace if you want to review saved jobs and outputs.