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Optimizing machine learning operations for scalable enterprise AI

Optimizing machine learning operations for scalable enterprise AI

Seamless data-driven decision delivery for enterprises

Seamless data-driven decision delivery for enterprises

Challenges slowing down MLOps success

Multiple friction points hinder the seamless AI scalability and integration

1

Data scientists rely heavily on IT teams for operationalization, creating bottlenecks

2

Ensuring models stay accurate and relevant over time remains a challenge

3

Models work in the lab but struggle in real-world deployment

4

Scalability and infrastructure complexity, slows things down

5

Long release timelines delay AI-driven business impact

Why enterprises need MLOps for scalable and efficient AI

MLOps keeps your AI scalable, efficient, and ready for real-world impact

MLOps: Streamlining AI from data to deployment

1

Continuous integration

  • Tests and validates code and components

  • Adds testing for data quality and integrity

  • Ensures models are validated before deployment

1

Continuous integration

  • Tests and validates code and components

  • Adds testing for data quality and integrity

  • Ensures models are validated before deployment

2

Continuous delivery

  • Automates deployment of trained models

  • Focuses on delivering a seamless ML training pipeline

  • Ensures a smooth transition to a live prediction service

2

Continuous delivery

  • Automates deployment of trained models

  • Focuses on delivering a seamless ML training pipeline

  • Ensures a smooth transition to a live prediction service

3

Continuous training

  • Designed specifically for ML systems

  • Automates model retraining based on new data

  • Enables seamless re-deployment of updated models

3

Continuous training

  • Designed specifically for ML systems

  • Automates model retraining based on new data

  • Enables seamless re-deployment of updated models

4

Continuous monitoring

  • Automates retraining as data evolves

  • Unique to ML systems and their lifecycle

  • Streamlines model re-deployment for continuous improvement

4

Continuous monitoring

  • Automates retraining as data evolves

  • Unique to ML systems and their lifecycle

  • Streamlines model re-deployment for continuous improvement

Fractal’s MLOps solutions: Powering scalable and efficient AI

Fractal’s MLOps solutions: Powering scalable and efficient AI

Fractal delivers AI automation across all major clouds with three engagement models

  • Full project 

  • Building MVP 

  • Staff augmentation 

1

Democratize model and artifacts

2

Effectively audit and monitor your models

3

Accelerate time-to-value and time-to-deployment

4

Decrease dependency on IT for model deployment

5

Increase model scalability during training and serving

6

Efficiently manage data error and model performance

7

Simplify model management, governance, deployment, and monitoring

Thought leadership

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Data drift: Identifying. Preventing. Automating

Disruption has given a new dimension to the data drift challenge. Businesses grappled with changing consumer behaviors, leading to changing data patterns

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Satellite image analytics — IVA Geo

Geospatial analysis leverages geographic data for decision-making

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From Inspection to Automation

The role of machine vision in modern manufacturing

Our experts

Snehotosh Banerjee

Lead ArchitectAI@Scale, Machine Vision and Conv. AI

Suraj Amonkar

Chief AI Research & Platforms Officer

Suraj Amonkar

Chief AI Research & Platforms Officer

Unlock the power of vision AI   

Unlock the power of vision AI   

Recognition and achievements

Select Fractal accolades

Named leader

Customer analytics service provider Q2 2025

Representative vendor

Customer analytics service provider Q1 2021

Great Place to Work

9th year running. Certifications received for India, USA, UK, and UAE

Recognition and achievements

Select Fractal accolades

Named leader

Customer analytics service provider Q2 2025

Representative vendor

Customer analytics service provider Q1 2021

Great Place to Work

9th year running. Certifications received for India, USA, UK, and UAE

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All rights reserved © 2026 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park,
Oberoi Garden City, Off W. E. Highway Goregaon (E),
Mumbai - 400063, Maharashtra, India.

Phone: +91 22 6850 5800

Email: investorrelations@fractal.ai

CIN : L72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

Privacy Policy

WB Policy

Supplier Code of Conduct

Terms of Use

Global Code of Conduct

OH&S Policy

Privacy & Cookies

Raise a concern

ESG Policy

Human Rights Statement

Modern Slavery Statement

CSR Policy

ABAC Policy