NextBrain AI

AutoML Cloud

AutoML Cloud

No-code predictive intelligence

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No-code

model building for business teams

Multi-step

analysis, training and deployment workflows

Operational

interfaces designed for production use

Benefits

Practical machine learning infrastructure for real operating teams

AutoML Cloud is designed to reduce friction between exploration, decision-making and deployment, while keeping the workflow readable enough for teams that need to move fast.

Connected pipeline

End-to-end machine learning without the usual handoffs

Import, clean, transform, analyze, train, visualize and share models from a single operational workspace. Teams stay inside one system instead of stitching together disconnected tools.

Connected pipeline

1

continuous workflow from raw data to deployment

Multi-source import and cleanupModel training and evaluationDashboards and deployment in one flow
AutoML workflow builder

Business focus

Surface the questions that move the business first

Instead of starting with model selection, NextBrain helps teams identify the business questions worth solving. That keeps experimentation tied to measurable outcomes from the beginning.

Business focus

Faster

alignment between analysts and decision-makers

Prioritize high-value use casesReduce noise in experimentationKeep model work outcome-driven
Business question discovery workspace

Natural interaction

Work with your data conversationally, not through friction

Explore datasets, ask questions and trigger advanced analysis through a more intuitive interface. The platform reduces the need for complex formulas and repetitive manual exploration.

Natural interaction

Lower

barrier for analysts and business teams

Natural-language explorationFaster insight generationLess dependency on specialist tooling
Conversational data interaction in AutoML Cloud

Operational deployment

Move from experimentation to collaboration and production cleanly

Share dashboards, models and progress across teams while keeping integrations practical. The platform is built to support real collaboration instead of isolated model work.

Operational deployment

Team-ready

handoff from analysis to operational use

Shared dashboards and model outputsPractical integrationsCleaner collaboration across teams
AutoML collaboration and deployment workspace

Usable by real teams

An interface that stays readable while the workflow gets more advanced

NextBrain bridges the gap between data scientists, analysts and operational stakeholders with an interface that remains understandable as models, assumptions and scenarios become more complex.

Usable by real teams

Clearer

visibility into decisions, models and assumptions

Low-friction model oversightReadable decision supportLess operational complexity
AutoML interface overview

Scenario intelligence

Run what-if analysis without rebuilding the process every time

Test different business scenarios, compare outcomes and assess tradeoffs quickly. This makes forecasting and counterfactual exploration much more practical for everyday work.

Scenario intelligence

Instant

scenario testing and outcome comparison

Scenario simulationCounterfactual explorationFaster planning decisions
What-if analysis in AutoML Cloud

Features

Built for teams that need machine learning to be usable

The platform combines data preparation, model development, deployment and extensions in one practical environment, reducing the usual complexity around production AI work.

Data preparation and importation

Data cleanup, import from SQL databases, APIs, CSV, Excel, SPSS, Google Sheets, Mongo and Dataslayer AI. Advanced import from multiple sources simultaneously, with scheduled dataset updates.

Model development and analytics

Classification, regression, time series forecasting with Bayesian modeling, multivariable forecasting, clustering, anomaly detection, counterfactual analysis, synthetic data generation, what-if analysis and causal analysis.

Deployment and accessibility

Interactive dashboards, prediction deployment on web app or iframe, configured Jupyter Notebook, deploy on your own server with Docker or autoscale with Kubernetes, plus open source code to automate training and prediction.

Integration and extensions

Multi-agent chat with code execution and ethernet capabilities, customizable with multiple LLMs such as OpenAI, Azure, Google Gemini, Mistral, LLaMa and Open Orca, with high-speed processing.

Privacy and security

Strong focus on data privacy with local models like Mistral or LLaMa for 100% privacy, SSO single sign-on technology and SOC2 certification in progress.

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