Auto ML

Still manually tuning every model?

Audit-grade AI anyone can build. iTuring Auto ML automates model building, tuning, and documentation—so you deliver business impact, fast.

Trusted by leading banks and insurers. Built for regulated industries with comprehensive documentation support.

Measurable Business Impact

Deploy compliant, production-ready models in weeks - not months

80%

Higher Approvals

Weeks vs Months

39%

Collection
Boost

2M+

Revenue
Impact

*Limited Slots

Banks and insurers using iTuring Auto ML report measurable impact in operational efficiency, compliance, and growth.

The Automation Process

How Automation Handles Your AI Lifecycle

Connect

Upload your data instantly (Any source, any format)

Compete

Algorithms compete for best performance (XGBoost, Random Forest, Neural Networks, more)

Crown

Best model selected automatically (Leaderboard highlights the champion)

Deploy

Production-ready in a few clicks. (Java, PMML, or API - your choice)

Platform Capabilities

Zero Risk. Maximum Control. Proven Results.

No Vendor Lock-in

Export models as Java, PMML, or API

Regulatory Compliant

Built-in audit trails and documentation

Expert Override

Manual control when you need it

Existing Infrastructure

Works with your current systems

Pick Your Mode

Choose Your Speed: Instant or Customized

Automated Mode

Single-click transforms raw data into production models. Perfect for business analysts and time-pressed teams.

Expert Mode

Manual control over sampling, missing treatment, outlier handling, transformations, and hyperparameters.

iTuring vs Others

Every Algorithm. Every Use Case. Full Regulatory Support.

Feature

Manual

Other AutoML

Time to Deploy

2-4 Weeks

3+ months

Algorithm Support

Limited by team

3-5 algorithms

Regulatory Docs

Manual creation

Limited support

Expert Control

Complete

Restricted

2-6 Hours

8 major algorithms

Automated

Full override

What You Get

Limited Time Offer

Frequently Asked Questions

What is Auto ML and how does it work?

Auto ML (Automated Machine Learning) automates your machine learning pipeline, from data preparation and feature engineering to model selection, tuning, and deployment. iTuring Auto ML enables rapid, audit-grade model deployment with built-in compliance support.

iTuring Auto ML typically delivers measurable ROI both in reduced project timelines and total cost of ownership compared to expanding in-house data science teams. Pricing details available on request.

Yes. iTuring Auto ML is designed for regulated industries, supporting audit trails, automated documentation, and explainability features as required by compliance teams.

iTuring supports major machine learning algorithms including XGBoost, Random Forest, Neural Networks, Logistic Regression (L1/L2), Stochastic Gradient Boosting, Light Gradient Boosting, and Naive Bayes for classification, regression, and anomaly detection.

No, Auto ML augments your team by automating routine tasks. Your data scientists can focus on strategy, business insights, and advanced model interpretation while Auto ML handles the repetitive work.

Full implementation typically takes 30-60 days, including data integration, team training, and first deployment. The pilot program enables model building within a few days of setup.

Yes. iTuring connects to SQL databases, NoSQL systems, Blob Storage, S3, HDFS, JSON files, and CSV uploads through pre-built connectors.

iTuring is built specifically for regulated industries, with comprehensive audit trails, documentation, and override by domain experts. It offers enterprise-grade security and industry-specific templates.

Our team will be happy to help you calculate ROI and build the business case to provide a clear view of average payback periods and total cost of ownership, supported by case studies.

Each client receives dedicated implementation and support, including a solution architect, data scientist, and customer success manager.

Is Auto ML secure enough for financial services data?
A: Yes. iTuring meets major financial services security requirements and can be deployed on-premise or in a private cloud. All data processing is encrypted at rest and in transit.