Federated Learning Solutions Market

Federated Learning Solutions Market is projected to reach USD 353 million by 2028, exhibiting a CAGR of 11.9% during forecast period.

Federated Learning Solutions Market Overview

Federated learning is the proposed framework that promises to solve most of the issues AI faces today, so AI and ML technologies can be further refined for the future. In layman’s terms, federated learning is a framework that proposes taking the singularity out of the ML process and expanding it across a selection of devices. Since most devices already have sophisticated technology, this theory proposes using it so that the AI has unrivaled access to data.

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Major Federated Learning Solutions Market Drivers

The factors driving the global Federated Learning Solutions market include its ability to enable companies to capitalize a shared Machine Learning (ML) model collaboratively by storing data on devices and allowing predictive features on smart devices without impacting the user experience and leaking private information. FL focuses on protecting users’ data by sharing model status. Companies can no longer ignore the rising importance of data privacy and data integrity. The perspective of federated learning has provided a new standard for applications leveraging data. Data silos and the emphasis on data privacy are essential challenges for AI, but FL could be a solution. It could develop a united model for multiple organizations while the local and sensitive data is protected to benefit together without having to worry about data privacy. FL has gained a lot of attention in how the technology tackles the challenge of protecting users’ privacy by decoupling data provisioned at end-user devices. Hence, the above-mentioned factors are aiding in the growth of federated learning solutions market share.

Restraint in the Federated Learning Solutions Market

However, the lack of trained employees is a key restraining factor responsible for hindering the growth of the federated learning solutions market. As it is a new concept, there is a lack of skilled people to develop and execute these projects involving complex techniques, such as ML.

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Application – Segment Analysis

Based on the Application, Industrial Internet of Things (IIoT) is expected to grow at a higher CAGR during the forecast period. Federated learning (FL) technology is implemented in IIoT by researchers to provide safe, accurate, robust, and unbiased models. Integrating FL in IIoT ensures that no local sensitive data is exchanged, as the distribution of learning models over the edge devices has become more familiar with FL. Therefore, only the encrypted notifications and parameters are communicated to the central server. In order to get valuable insights and patterns from the data generated by IoT devices in IIoT applications, ML and DL algorithms are used. These algorithms are trained regularly by large datasets collected from different industries to understand the complex patterns from the data generated. These datasets need not be transferred to the central location for training the algorithms when FL is used. Hence it secures sensitive data from potential hackers. Furthermore, the sensors in IIoT applications generate a massive amount of data stored in the edge devices for analytics and then moved to a centralized location like the cloud, but with FL, the entire data need not be transferred to the cloud. Instead, only the summarized results after applying the ML model are transferred to the cloud, which reduces the communication cost for transferring the data to the cloud.

Vertical – Segment Analysis

Based on the Vertical, the Manufacturing segment is projected to dominate the market during the forecast period. With the increasing attention on Industrial Internet of Things (IIoT) and the rise in competition, manufacturing companies prioritize the analysis of data collected from numerous sources, including web, mobile, stores, and social media. One of the main advantages of IIoT is the ability to increase efficiency through prediction. For example, the sensors in the manufacturing plant machines can automatically pinpoint precisely where and what the trouble is and can automatically place a service request. Until recently, manufacturing companies use to spend significant capital on purchasing and maintenance of equipment. But with the advancements in IIoT, the industries can lease the equipment from vendors. The owners can remotely monitor these equipments through the sensors, thereby delivering upgrades, repairs and maintenance remotely.

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Regional – Segment Analysis:

Based on the region, the Asia-Pacific region is expected to grow at a higher CAGR during the forecast period. The increase in the adoption of disruptive technologies, like big data analytics, AI, and IoT, and ongoing evolution to introduce data regulations, as well as focus on hyper-personalization and contextual recommendation in support of budding eCommerce markets in APAC countries like China, India, and Japan are expected to drive the growth of federated learning solutions size in the region.

Top Market Players

Various notable players operating in the market, include, NVIDIA Corporation, Cloudera, Inc., Microsoft, OWKIN, INC., Intellegens Limited, Edge Delta, Inc., Enveil, SECURE AI LABS, INC., sherpa.ai, Consilient, among others. 

Key Developments:

• • In 2021, NVIDIA Corporation launched the NVIDIA AI Enterprise, a complete software suite of enterprise-grade AI tools and frameworks optimized, certified, and approved by NVIDIA that run on VMware vSphere. NVIDIA AI Enterprise offers customers to reduce AI model development time from 80 weeks to just eight weeks and allows them to install and operate advanced AI applications on VMware vSphere.
  • In 2021, Enveil launched a new version of ZeroReveal 3.0. It presents homomorphic encryption-powered capabilities through an efficient and decentralized framework designed to reduce risk and address business challenges, including data sharing, collaboration, monetization, and regulatory compliance. The solution enhancements delivered in 3.0 releases strengthen integration, performance, and user experience features for both Enveil’s ZeroReveal Search and ZeroReveal Machine Learning product lines.
  • In May 2020, OWKIN launched the COVID-19 Open AI Consortium (COAI). The consortium will enable advanced collaborative research and accelerate the clinical development of effective treatments for patients who are infected with COVID-19. In this project, Owkin used federated learning, aiming to help healthcare companies understand why drug efficacy varies from patient to patient, embrace the drug development process and identify the best drug for the right patient at the right time.

Segments covered in the Report:

The global Federated Learning Solutions market has been segmented on the basis of Application, Vertical and regions. Based on Application, the market is segmented into Drug Discovery, Data privacy and Security Management, Risk Management, Shopping Experience Personalization, Industrial Internet of Things (IIoT), Online Visual Object Detection and Other. Based on Vertical, the market is segmented into BFSI, Healthcare and Life Sciences, Retail and eCommerce, Manufacturing, Energy and Utilities and Other. 

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Market Segmentation

Global Federated Learning Solutions Market by Application

• • Drug Discovery
  • Data privacy and Security Management
  • Risk Management
  • Shopping Experience Personalization
  • Industrial Internet of Things (IIoT)
  • Online Visual Object Detection
  • Other

Global Federated Learning Solutions Market by Vertical

• • BFSI
  • Healthcare and Life Sciences
  • Retail and eCommerce
  • Manufacturing
  • Energy and Utilities
  • Other

Global Federated Learning Solutions Market by Region

• • North America Federated Learning Solutions Market (Option 1: As a part of the free 25% customization)

    • North America Federated Learning Solutions Market by Application
    • North America Federated Learning Solutions Market by Vertical
    • US Federated Learning Solutions Market All-Up
    • Canada Federated Learning Solutions Market All-Up

  • Europe Federated Learning Solutions Market (Option 2: As a part of the free 25% customization)

    • Europe Federated Learning Solutions Market by Application
    • Europe Federated Learning Solutions Market by Vertical
    • UK Federated Learning Solutions Market All-Up
    • Germany Federated Learning Solutions Market All-Up
    • France Federated Learning Solutions Market All-Up
    • Spain Federated Learning Solutions Market All-Up
    • Rest of Europe Federated Learning Solutions Market All-Up

  • Asia-Pacific Federated Learning Solutions Market (Option 3: As a part of the free 25% customization)

    • Asia-Pacific Federated Learning Solutions Market by Application
    • Asia-Pacific Federated Learning Solutions Market by Vertical
    • China Federated Learning Solutions Market All-Up
    • India Federated Learning Solutions Market All-Up
    • Japan Federated Learning Solutions Market All-Up
    • Rest of APAC Federated Learning Solutions Market All-Up

  • RoW Federated Learning Solutions Market (Option 4: As a part of the free 25% customization)

    • RoW Federated Learning Solutions Market by Application
    • RoW Federated Learning Solutions Market by Vertical
    • Brazil Federated Learning Solutions Market All-Up
    • South Africa Federated Learning Solutions Market All-Up
    • Saudi Arabia Federated Learning Solutions Market All-Up
    • UAE Federated Learning Solutions Market All-Up
    • Rest of world (remaining countries of the LAMEA region) Federated Learning Solutions Market All-Up

Major Players Operating in the Federated Learning Solutions (Option 5: As a part of the Free 25% Customization – Profiles of 5 Additional Companies of your Choice)

• • NVIDIA Corporation
  • Cloudera, Inc.
  • Microsoft
  • OWKIN, INC.
  • Intellegens Limited
  • Edge Delta, Inc.
  • Enveil
  • SECURE AI LABS, INC.
  • sherpa.ai
  • Consilient