Global Multimodal Al Market Size, Share & Industry Trends Analysis Report By Offering, By Type (Generative, Translative, Interactive, and Explanatory), By Technology, By Data Modality, By Vertical, By Regional Outlook and Forecast, 2023 - 2030

Global Multimodal Al Market Size, Share & Industry Trends Analysis Report By Offering, By Type (Generative, Translative, Interactive, and Explanatory), By Technology, By Data Modality, By Vertical, By Regional Outlook and Forecast, 2023 - 2030


The Global Multimodal Al Market size is expected to reach $8.4 billion by 2030, rising at a market growth of 32.3% CAGR during the forecast period.

Multimodal AI assists content creators in generating and editing media content by analyzing various modalities, including text, images, and audio. Therefore, the media & entertainment segment acquired $84.2 million in 2022. It assists content creators in generating and editing media content by analyzing various modalities, including text, images, and audio. It automatically analyzes audio, video, and image content to generate descriptive tags and metadata. This facilitates content organization, search, and recommendation systems. It interprets spoken language and voice inputs, enabling applications like voice-controlled interfaces, voice search, and voice-activated assistants. It improves the viewing experience, enables instant replay, and enhances sports analytics.

The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In, December, 2023, Amazon Web Services, Inc. a company of Amazon, Inc. has launched Amazon Q. With 17 years of AWS experience under its belt, Amazon Q is well-equipped to help consumers navigate the AWS administration panel and other AWS features. Additionally, In, November, 2023, Microsoft corporation has unveiled new AI-powered copilots for AI assistant to transform your way of work. Copilot is going to provide assistance in the context and intelligence of the web, with your privacy and security at priority.

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Market. In, November, 2023, Microsoft Corporation has expanded its range of Azure AI products by introducing new features in both generative and traditional AI capabilities. Developers can leverage Azure AI Studio, equipped with configurable tooling and models, to design innovative generative AI applications, including those incorporating Microsoft's Copilot generative AI assistant. Companies such as Meta Platforms, Inc., IBM Corporation are some of the key innovators in Market.

Market Growth Factors

Generative AI techniques to accelerate multimodal ecosystem development

Generative AI is like the creative powerhouse of the AI world, capable of producing new content such as text, images, or even entire videos. It can create content that combines multiple data formats. For instance, it can generate detailed written descriptions for images, create realistic images from textual descriptions, or even produce videos with a nuanced understanding of the content. This blending of data formats is where Generative AI and multimodal AI synergize. As Generative AI advances, it not only enhances the creative aspects of multimodal AI but also paves the way for more sophisticated, integrated systems. Moreover, it can automate the creation of multimedia presentations, making them more impactful and informative. These aspects will boost market growth in the coming years.

Rising demand for customized and industry-specific solutions

Different industries have distinct workflows, regulations, and operational requirements. Customized solutions are designed to accommodate these specific needs, ensuring optimal functionality. Industries often operate under specific regulatory frameworks. Customized solutions can be developed to ensure compliance with industry norms and regulations, minimizing the risk of non-compliance. Custom solutions can be tailored to integrate seamlessly into existing workflows, automate processes, and enhance efficiency. This leads to increased productivity and reduces operational costs. The industries with direct customer interactions benefit from customized solutions that align with customer preferences, improving customer satisfaction. Thus, the rising demand for customized and industry-specific solutions expands the market growth.

Market Restraining Factors

Susceptibility to bias in multimodal models

Multimodal AI models, like their unimodal counterparts, are vulnerable to bias, which often originates from the data they are trained on. Training datasets, comprising text, images, videos, and more, may inadvertently reflect societal or cultural biases in the data sources. These biases can manifest in numerous ways, such as gender or racial bias in image recognition or linguistic and contextual bias in natural language processing tasks. When multimodal AI models are trained on such data, they inevitably inherit and perpetuate these biases, which can lead to inaccurate or unfair outcomes when making predictions or decisions. It also necessitates an ongoing commitment to ethical AI development and the responsible use of these technologies, ensuring that AI systems are technically proficient and aligned with ethical and societal values. Hence, the above aspects will hamper market growth in the coming years.

Offering Outlook

On the basis of offering, the market is segmented into solution and services. In 2022, the solution segment dominated the market with the maximum revenue share. Solutions for implementing multimodal AI in smart city initiatives include traffic management, public safety applications, and environmental monitoring using data from various sensors and cameras. Solutions are designed to analyze medical imaging data, incorporating modalities such as MRI, CT scans, and X-rays. These solutions assist in medical diagnosis and treatment planning. Solutions specifically designed for processing and analyzing speech and audio data. This includes speech recognition, natural language processing for audio, and voice biometrics.

Solution Outlook

Under solutions type, the market is further divided into framework, platform, and software. In 2022, the platform segment dominated the market with the maximum revenue share. Such platforms provide a unified environment where developers, data scientists, and businesses can leverage various AI modalities (text, image, speech, etc.) to create sophisticated and interconnected AI systems. Platform solutions in the market aim to simplify the development process, promote collaboration, and enable businesses to harness the power of diverse data types for more advanced and context-aware AI applications.

Type Outlook

On the basis of type, the market is classified into generative, translative, explanatory, and interactive. The translative multimodal AI segment recorded a remarkable revenue share in the market in 2022. This term could imply the integration of translation capabilities with multimodal AI, suggesting a system that not only translates text but also understands and processes information from multiple modalities. Translating videos, presentations, or documents that contain a combination of text, images, and audio.

Technology Outlook

By technology, the market is categorized into machine learning, natural language processing, computer vision, context awareness, and internet of things. In 2022, the natural language processing segment registered the highest revenue share in the market. Natural Language Processing (NLP) is a field of AI focusing on the interaction between computers and human language. It involves the development of algorithms and models that enable computers to understand, interpret, and generate human-like text. NLP encompasses many tasks and applications, from simple tasks like language translation to more complex ones like sentiment analysis and text summarization.

Data Modality Outlook

Based on data modality, the market is fragmented into text data, speech & voice data, image data, video data, and audio data. The video data segment recorded a remarkable revenue share in the market in 2022. Videos are composed of individual frames, each representing a still image. The rapid succession of frames creates the illusion of motion. Video data modality is integral to various applications, including video content analysis, surveillance, entertainment, education, and healthcare. As technology advances, video analysis capabilities in AI systems are expected to improve further, enabling a more sophisticated understanding of dynamic scenes and human activities.

Vertical Outlook

Based on vertical, the market is divided into BFSI, retail & eCommerce, telecommunications, government & public sector, healthcare & life sciences, manufacturing, automotive, transportation & logistics, media & entertainment, and others. The retail & eCommerce segment acquired a substantial revenue share in the market in 2022. AI-powered virtual try-on solutions enable customers to visualize how products like clothing, accessories, or even furniture will look on them or in their homes using augmented reality (AR). It analyzes customer behavior, including browsing history, purchase patterns, and interactions with different media types. This information is then used to provide personalized product recommendations. Increases cross-selling and upselling opportunities, improves customer satisfaction, and enhances conversion rates.

Regional Outlook

Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region held the highest revenue share in the market. The market in North America stands as a global powerhouse, shaped by the innovation and technological ability of the US and Canada. The region's focus on innovation, particularly in Silicon Valley, fosters a conducive environment for multimodal AI advancements. North American companies are at the forefront of developing and implementing multimodal AI solutions, reflecting the region's commitment to driving technological advancements and pushing the boundaries of artificial intelligence for enhanced user engagement and problem-solving.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google LLC (Alphabet, Inc.), Microsoft Corporation, OpenAI, L.L.C., Meta Platforms, Inc. (Meta), Amazon Web Services, Inc. (Amazon.com, Inc.), IBM Corporation, Twelve Labs Inc., Aimesoft Inc., Jina AI GmbH, and Uniphore Technologies Inc.

Recent Strategies Deployed in Multimodal AI Market

Partnerships, Collaborations & Agreements:

Nov-2023: IBM Corporation and NASA have joined forces to create a collaborative partnership. The focus of this collaboration is the development of a geospatial artificial intelligence (AI) model dedicated to climate and weather observation. Anticipated benefits of this collaboration include enhanced accessibility, improved accuracy, faster processing times, and a more diverse range of data when compared to existing AI models such as GraphCast and Fourcastnet. The aim is to elevate the capabilities of weather forecasting through the integration of advanced AI technology.

Apr-2023: Google cloud a division of Google LLC. formed a collaboration with Care AI Inc., an AI driven Smart Care Facility Platform in healthcare. Under this collaboration, the companies are intended to make it easier for users to access Care AI's Virtual Nursing Solution on Google Cloud Marketplace and revolutionize the healthcare industry.

Mar-2023: Amazon Web Services Inc., a subsidiary of Amazon.com, Inc., has partnered with NVIDIA Corporation, a technology company specializing in graphics processors and mobile technologies. In this collaborative effort, NVIDIA aims to create the world's most scalable AI infrastructure tailored for training complex large language models (LLMs). The collaboration involves the development of Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, which are equipped with NVIDIA H100 Tensor Core GPUs and leverage AWS's advanced networking and scalability features. This collaboration is set to deliver an impressive computing power of up to 20 exaFLOPS, facilitating the construction and training of the most extensive deep learning models.

Feb-2023: Uniphore Technologies Inc. has successfully finalized the purchase of Hexagone AB, a prominent player in digital reality solutions that integrates sensor, software, and autonomous technologies to leverage data effectively. This strategic acquisition empowers Uniphore to incorporate significant improvements in behavioural science into its acclaimed X Platform. The integration ensures that customer interactions and inquiries are addressed with heightened accuracy and empathy.

Feb-2023: Uniphore Technologies Inc. has successfully acquired Red Box, a leading open corporate platform specializing in the recording of audio, video, and metadata from conversations. This strategic move allows Uniphore to integrate Red Box's established expertise in capturing and securing real-time and post-call voice and screen interactions into its portfolio. This enhancement will further strengthen the capabilities of the Uniphore X platform, a trusted solution for global enterprises seeking to derive value from every conversation.

Apr-2022: Uniphore Technologies Inc. has acquired Colabo, a software company known for its AI-powered knowledge automation solution, which focuses on extracting information from both structured and unstructured documents in real time. By integrating Colabo's solution into Uniphore's conversational automation platform, enterprises can now use AI to extract knowledge entities and graphs from various data types, ensuring more relevant content and improved customer interactions for IVAs and live agents.

Product Launches and Product Expansion:

Dec-2023: Amazon Web Services, Inc a Company of Amazon, Inc. has launched Amazon Q, a generative AI assistant. Based on inquiries from customers in real time, Amazon Q gives customer support representatives suggested answers and actions. With 17 years of AWS experience under its belt, Amazon Q is well-equipped to help consumers navigate the AWS administration panel and other AWS features.

Nov-2023: Microsoft corporation has unveiled new AI-powered copilots for their most used products like GitHub, Microsoft 365, Bing and Edge. Microsoft 365 Copilot will be available with AI assistant to transform your way of work. Copilot is going to provide assistance in the context and intelligence of the web, with your privacy and security at priority.

Nov-2023: Microsoft Corporation has expanded its range of Azure AI products by introducing new features in both generative and traditional AI capabilities. Developers can leverage Azure AI Studio, equipped with configurable tooling and models, to design innovative generative AI applications, including those incorporating Microsoft's Copilot generative AI assistant.

Aug-2023: IBM Corporation unveiled a new generative AI-assisted product called Watsonx Code Assistant for Z, which help in enable faster translation of COBOL to Java on IBM Z. through this product launch IBM aims to accelerate code development and increasing developer productivity, throughout the application modernization lifecycle.

Aug-2023: Meta Platform Inc. introduces SeamlessM4T, a cutting-edge AI translation model that excels in both multimodal and multilingual capabilities. The company has unveiled this groundbreaking product through a research license, enabling researchers and developers to leverage the platform and facilitate seamless communication through text and speech across different languages. SeamlessM4T boasts Speech-to-text translation functionality for nearly 100 input and output languages, along with Speech-to-speech translation support for 100 input and 30 output languages.

May-2023: Google LLC has introduced PaLM2, an advanced language model designed for diverse applications. PaLM2 serves as a versatile AI model capable of generating chatbots akin to ChatGPT, coding in multiple languages, language translation, and photo analysis with corresponding reactions. Users can employ PaLM2 to search for restaurants in Bulgaria in English, wherein the system will seek Bulgarian responses on the web, retrieve an answer, translate it into English, attach a location photo, and present the result to the user in English.

Apr-2023: Microsoft Corporation has launched JARVIS, a multimodal AI-powered platform. JARVIS is developed in such a way that it can collaborate and connect with multiple AI models, like ChatGPT and t5-base. Users can take demo of JARVIS on AI platform Huggingface. JARVIS adds multiple open-source LLMs for photos, videos, audio, and more, extending OpenAI's GPT-4 multimodal capabilities, as shown through text and image processing.

Mar-2023: OpenAI, LLC has launched a new GPT-4 language model for ChatGPT as part of extending its capabilities. As GPT-4 is working on multimodal AI now it can accept both text and image as input and gives output as text to user. With GPT-4's image processing capability now it can also help you generate a packing list for upcoming trip, with the help of photo of your closet.

Jun-2022: Aimesoft launched AimeFluent, a chatbot development library for the game engine Unity. AimeFluent gives non-player characters (NPCs) the ability to respond to user input text automatically. AimeFluent is an NLP based platform that works on rule-based, scenario-based, or information-retreival-based methods to understand and reply to user inputs.

Sep-2021: Aimesoft has unveiled AimeTalk, an AI automated slide presentation software tool. AimeTalk has the ability to read speaker's notes with the help of Text-to-Speech technology and creating a face animated video for presentation with the help of advance image processing and computer vision technology. AimeTalk can automatically give error free presentation by using Artificial Intelligence and Robotic Process Automation, thus saving lot of time.

June-2021: Aimesoft has launched AimeLytics, an AI based analytics platform. AimeLytics can be utilized for voice analytics (emotion identification from speech, speech summarization, etc.), text mining (document classification, sentiment analysis), and predictive analytics (revenue forecast, KPI prediction, stock prediction, etc.). Aimelytics can also be used for high precision combination of text, speech, image, and numerical data into one AI model.

Merger & Acquisitions:

Feb-2023: Uniphore Technologies Inc. has successfully finalized the purchase of Hexagone AB, a prominent player in digital reality solutions that integrates sensor, software, and autonomous technologies to leverage data effectively. This strategic acquisition empowers Uniphore to incorporate significant improvements in behavioural science into its acclaimed X Platform. The integration ensures that customer interactions and inquiries are addressed with heightened accuracy and empathy.

Feb-2023: Uniphore Technologies Inc. has successfully acquired Red Box, a leading open corporate platform specializing in the recording of audio, video, and metadata from conversations. This strategic move allows Uniphore to integrate Red Box's established expertise in capturing and securing real-time and post-call voice and screen interactions into its portfolio. This enhancement will further strengthen the capabilities of the Uniphore X platform, a trusted solution for global enterprises seeking to derive value from every conversation.

Apr-2022: Uniphore Technologies Inc. has acquired Colabo, a software company known for its AI-powered knowledge automation solution, which focuses on extracting information from both structured and unstructured documents in real time. By integrating Colabo's solution into Uniphore's conversational automation platform, enterprises can now use AI to extract knowledge entities and graphs from various data types, ensuring more relevant content and improved customer interactions for IVAs and live agents.

Geographical Expansions:

Jun-2020: Aimesoft has announced the expansion of its global footprints with opening of Aimesoft Japan. Under this expansion, the company want to increase its business in Japan and reach-out broad spectrum of customers.

Scope of the Study

Market Segments covered in the Report:

By Offering
  • Solution
  • Solution Deployment Type
  • Cloud
  • On-premise
  • Solution Type
  • Platform
  • Software
  • Framework
  • Services
By Type
  • Generative
  • Translative
  • Interactive
  • Explanatory
By Technology
  • Natural Language Processing
  • Machine Learning
  • Computer Vision
  • Context Awareness
  • Internet of Things
By Data Modality
  • Image Data
  • Video Data
  • Text Data
  • Speech & Voice Data
  • Audio Data
By Vertical
  • BFSI
  • Government & Public Sector
  • Automotive, Transportation & Logistics
  • Healthcare & Lifesciences
  • Media & Entertainment
  • Manufacturing
  • Retail & eCommerce
  • Telecommunications
  • Others
By Geography
  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA
Companies Profiled
  • Google LLC (Alphabet, Inc.)
  • Microsoft Corporation
  • OpenAI, L.L.C.
  • Meta Platforms, Inc. (Meta)
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • IBM Corporation
  • Twelve Labs Inc.
  • Aimesoft Inc.
  • Jina AI GmbH
  • Uniphore Technologies Inc.
Unique Offerings from KBV Research
  • Exhaustive coverage
  • Highest number of market tables and figures
  • Subscription based model available
  • Guaranteed best price
  • Assured post sales research support with 10% customization free


Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Multimodal AI Market, by Offering
1.4.2 Global Multimodal AI Market, by Type
1.4.3 Global Multimodal AI Market, by Technology
1.4.4 Global Multimodal AI Market, by Data Modality
1.4.5 Global Multimodal AI Market, by Vertical
1.4.6 Global Multimodal AI Market, by Geography
1.5 Methodology for the research
Chapter 2. Market at a Glance
2.1 Key Highlights
Chapter 3. Market Overview
3.1 Introduction
3.1.1 Overview
3.1.1.1 Market Composition and Scenario
3.2 Key Factors Impacting the Market
3.2.1 Market Drivers
3.2.2 Market Restraints
Chapter 4. Competition Analysis - Global
4.1 KBV Cardinal Matrix
4.2 Recent Industry Wide Strategic Developments
4.2.1 Partnerships, Collaborations and Agreements
4.2.2 Product Launches and Product Expansions
4.2.3 Acquisition and Mergers
4.2.4 Geographical Expansion
4.3 Market Share Analysis, 2022
4.4 Top Winning Strategies
4.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
4.4.2 Key Strategic Move: (Product Launches and Product Expansions: 2021, Jun – 2023, Dec) Leading Players
4.5 Porter’s Five Forces Analysis
Chapter 5. Global Multimodal AI Market by Offering
5.1 Global Solution Market by Region
5.2 Global Multimodal AI Market by Solution Deployment Type
5.2.1 Global Cloud Market by Region
5.2.2 Global On-premise Market by Region
5.3 Global Multimodal AI Market by Solution Type
5.3.1 Global Platform Market by Region
5.3.2 Global Software Market by Region
5.3.3 Global Framework Market by Region
5.4 Global Services Market by Region
Chapter 6. Global Multimodal AI Market by Type
6.1 Global Generative Market by Region
6.2 Global Translative Market by Region
6.3 Global Interactive Market by Region
6.4 Global Explanatory Market by Region
Chapter 7. Global Multimodal AI Market by Technology
7.1 Global Natural Language Processing Market by Region
7.2 Global Machine Learning Market by Region
7.3 Global Computer Vision Market by Region
7.4 Global Context Awareness Market by Region
7.5 Global Internet of Things Market by Region
Chapter 8. Global Multimodal AI Market by Data Modality
8.1 Global Image Data Market by Region
8.2 Global Video Data Market by Region
8.3 Global Text Data Market by Region
8.4 Global Speech & Voice Data Market by Region
8.5 Global Audio Data Market by Region
Chapter 9. Global Multimodal AI Market by Vertical
9.1 Global BFSI Market by Region
9.2 Global Government & Public Sector Market by Region
9.3 Global Automotive, Transportation & Logistics Market by Region
9.4 Global Healthcare & Lifesciences Market by Region
9.5 Global Media & Entertainment Market by Region
9.6 Global Manufacturing Market by Region
9.7 Global Retail & eCommerce Market by Region
9.8 Global Telecommunications Market by Region
9.9 Global Others Market by Region
Chapter 10. Global Multimodal AI Market by Region
10.1 North America Multimodal AI Market
10.1.1 North America Multimodal AI Market by Offering
10.1.1.1 North America Solution Market by Region
10.1.1.2 North America Multimodal AI Market by Solution Deployment Type
10.1.1.2.1 North America Cloud Market by Region
10.1.1.2.2 North America On-premise Market by Region
10.1.1.3 North America Multimodal AI Market by Solution Type
10.1.1.3.1 North America Platform Market by Country
10.1.1.3.2 North America Software Market by Country
10.1.1.3.3 North America Framework Market by Country
10.1.1.4 North America Services Market by Region
10.1.2 North America Multimodal AI Market by Type
10.1.2.1 North America Generative Market by Country
10.1.2.2 North America Translative Market by Country
10.1.2.3 North America Interactive Market by Country
10.1.2.4 North America Explanatory Market by Country
10.1.3 North America Multimodal AI Market by Technology
10.1.3.1 North America Natural Language Processing Market by Country
10.1.3.2 North America Machine Learning Market by Country
10.1.3.3 North America Computer Vision Market by Country
10.1.3.4 North America Context Awareness Market by Country
10.1.3.5 North America Internet of Things Market by Country
10.1.4 North America Multimodal AI Market by Data Modality
10.1.4.1 North America Image Data Market by Country
10.1.4.2 North America Video Data Market by Country
10.1.4.3 North America Text Data Market by Country
10.1.4.4 North America Speech & Voice Data Market by Country
10.1.4.5 North America Audio Data Market by Country
10.1.5 North America Multimodal AI Market by Vertical
10.1.5.1 North America BFSI Market by Country
10.1.5.2 North America Government & Public Sector Market by Country
10.1.5.3 North America Automotive, Transportation & Logistics Market by Country
10.1.5.4 North America Healthcare & Lifesciences Market by Country
10.1.5.5 North America Media & Entertainment Market by Country
10.1.5.6 North America Manufacturing Market by Country
10.1.5.7 North America Retail & eCommerce Market by Country
10.1.5.8 North America Telecommunications Market by Country
10.1.5.9 North America Others Market by Country
10.1.6 North America Multimodal AI Market by Country
10.1.6.1 US Multimodal AI Market
10.1.6.1.1 US Multimodal AI Market by Offering
10.1.6.1.2 US Multimodal AI Market by Type
10.1.6.1.3 US Multimodal AI Market by Technology
10.1.6.1.4 US Multimodal AI Market by Data Modality
10.1.6.1.5 US Multimodal AI Market by Vertical
10.1.6.2 Canada Multimodal AI Market
10.1.6.2.1 Canada Multimodal AI Market by Offering
10.1.6.2.2 Canada Multimodal AI Market by Type
10.1.6.2.3 Canada Multimodal AI Market by Technology
10.1.6.2.4 Canada Multimodal AI Market by Data Modality
10.1.6.2.5 Canada Multimodal AI Market by Vertical
10.1.6.3 Mexico Multimodal AI Market
10.1.6.3.1 Mexico Multimodal AI Market by Offering
10.1.6.3.2 Mexico Multimodal AI Market by Type
10.1.6.3.3 Mexico Multimodal AI Market by Technology
10.1.6.3.4 Mexico Multimodal AI Market by Data Modality
10.1.6.3.5 Mexico Multimodal AI Market by Vertical
10.1.6.4 Rest of North America Multimodal AI Market
10.1.6.4.1 Rest of North America Multimodal AI Market by Offering
10.1.6.4.2 Rest of North America Multimodal AI Market by Type
10.1.6.4.3 Rest of North America Multimodal AI Market by Technology
10.1.6.4.4 Rest of North America Multimodal AI Market by Data Modality
10.1.6.4.5 Rest of North America Multimodal AI Market by Vertical
10.2 Europe Multimodal AI Market
10.2.1 Europe Multimodal AI Market by Offering
10.2.1.1 Europe Solution Market by Country
10.2.1.2 Europe Multimodal AI Market by Solution Deployment Type
10.2.1.2.1 Europe Cloud Market by Country
10.2.1.2.2 Europe On-premise Market by Country
10.2.1.3 Europe Multimodal AI Market by Solution Type
10.2.1.3.1 Europe Platform Market by Country
10.2.1.3.2 Europe Software Market by Country
10.2.1.3.3 Europe Framework Market by Country
10.2.1.4 Europe Services Market by Country
10.2.2 Europe Multimodal AI Market by Type
10.2.2.1 Europe Generative Market by Country
10.2.2.2 Europe Translative Market by Country
10.2.2.3 Europe Interactive Market by Country
10.2.2.4 Europe Explanatory Market by Country
10.2.3 Europe Multimodal AI Market by Technology
10.2.3.1 Europe Natural Language Processing Market by Country
10.2.3.2 Europe Machine Learning Market by Country
10.2.3.3 Europe Computer Vision Market by Country
10.2.3.4 Europe Context Awareness Market by Country
10.2.3.5 Europe Internet of Things Market by Country
10.2.4 Europe Multimodal AI Market by Data Modality
10.2.4.1 Europe Image Data Market by Country
10.2.4.2 Europe Video Data Market by Country
10.2.4.3 Europe Text Data Market by Country
10.2.4.4 Europe Speech & Voice Data Market by Country
10.2.4.5 Europe Audio Data Market by Country
10.2.5 Europe Multimodal AI Market by Vertical
10.2.5.1 Europe BFSI Market by Country
10.2.5.2 Europe Government & Public Sector Market by Country
10.2.5.3 Europe Automotive, Transportation & Logistics Market by Country
10.2.5.4 Europe Healthcare & Lifesciences Market by Country
10.2.5.5 Europe Media & Entertainment Market by Country
10.2.5.6 Europe Manufacturing Market by Country
10.2.5.7 Europe Retail & eCommerce Market by Country
10.2.5.8 Europe Telecommunications Market by Country
10.2.5.9 Europe Others Market by Country
10.2.6 Europe Multimodal AI Market by Country
10.2.6.1 Germany Multimodal AI Market
10.2.6.1.1 Germany Multimodal AI Market by Offering
10.2.6.1.2 Germany Multimodal AI Market by Type
10.2.6.1.3 Germany Multimodal AI Market by Technology
10.2.6.1.4 Germany Multimodal AI Market by Data Modality
10.2.6.1.5 Germany Multimodal AI Market by Vertical
10.2.6.2 UK Multimodal AI Market
10.2.6.2.1 UK Multimodal AI Market by Offering
10.2.6.2.2 UK Multimodal AI Market by Type
10.2.6.2.3 UK Multimodal AI Market by Technology
10.2.6.2.4 UK Multimodal AI Market by Data Modality
10.2.6.2.5 UK Multimodal AI Market by Vertical
10.2.6.3 France Multimodal AI Market
10.2.6.3.1 France Multimodal AI Market by Offering
10.2.6.3.2 France Multimodal AI Market by Type
10.2.6.3.3 France Multimodal AI Market by Technology
10.2.6.3.4 France Multimodal AI Market by Data Modality
10.2.6.3.5 France Multimodal AI Market by Vertical
10.2.6.4 Russia Multimodal AI Market
10.2.6.4.1 Russia Multimodal AI Market by Offering
10.2.6.4.2 Russia Multimodal AI Market by Type
10.2.6.4.3 Russia Multimodal AI Market by Technology
10.2.6.4.4 Russia Multimodal AI Market by Data Modality
10.2.6.4.5 Russia Multimodal AI Market by Vertical
10.2.6.5 Spain Multimodal AI Market
10.2.6.5.1 Spain Multimodal AI Market by Offering
10.2.6.5.2 Spain Multimodal AI Market by Type
10.2.6.5.3 Spain Multimodal AI Market by Technology
10.2.6.5.4 Spain Multimodal AI Market by Data Modality
10.2.6.5.5 Spain Multimodal AI Market by Vertical
10.2.6.6 Italy Multimodal AI Market
10.2.6.6.1 Italy Multimodal AI Market by Offering
10.2.6.6.2 Italy Multimodal AI Market by Type
10.2.6.6.3 Italy Multimodal AI Market by Technology
10.2.6.6.4 Italy Multimodal AI Market by Data Modality
10.2.6.6.5 Italy Multimodal AI Market by Vertical
10.2.6.7 Rest of Europe Multimodal AI Market
10.2.6.7.1 Rest of Europe Multimodal AI Market by Offering
10.2.6.7.2 Rest of Europe Multimodal AI Market by Type
10.2.6.7.3 Rest of Europe Multimodal AI Market by Technology
10.2.6.7.4 Rest of Europe Multimodal AI Market by Data Modality
10.2.6.7.5 Rest of Europe Multimodal AI Market by Vertical
10.3 Asia Pacific Multimodal AI Market
10.3.1 Asia Pacific Multimodal AI Market by Offering
10.3.1.1 Asia Pacific Solution Market by Country
10.3.1.2 Asia Pacific Multimodal AI Market by Solution Deployment Type
10.3.1.2.1 Asia Pacific Cloud Market by Country
10.3.1.2.2 Asia Pacific On-premise Market by Country
10.3.1.3 Asia Pacific Multimodal AI Market by Solution Type
10.3.1.3.1 Asia Pacific Platform Market by Country
10.3.1.3.2 Asia Pacific Software Market by Country
10.3.1.3.3 Asia Pacific Framework Market by Country
10.3.1.4 Asia Pacific Services Market by Country
10.3.2 Asia Pacific Multimodal AI Market by Type
10.3.2.1 Asia Pacific Generative Market by Country
10.3.2.2 Asia Pacific Translative Market by Country
10.3.2.3 Asia Pacific Interactive Market by Country
10.3.2.4 Asia Pacific Explanatory Market by Country
10.3.3 Asia Pacific Multimodal AI Market by Technology
10.3.3.1 Asia Pacific Natural Language Processing Market by Country
10.3.3.2 Asia Pacific Machine Learning Market by Country
10.3.3.3 Asia Pacific Computer Vision Market by Country
10.3.3.4 Asia Pacific Context Awareness Market by Country
10.3.3.5 Asia Pacific Internet of Things Market by Country
10.3.4 Asia Pacific Multimodal AI Market by Data Modality
10.3.4.1 Asia Pacific Image Data Market by Country
10.3.4.2 Asia Pacific Video Data Market by Country
10.3.4.3 Asia Pacific Text Data Market by Country
10.3.4.4 Asia Pacific Speech & Voice Data Market by Country
10.3.4.5 Asia Pacific Audio Data Market by Country
10.3.5 Asia Pacific Multimodal AI Market by Vertical
10.3.5.1 Asia Pacific BFSI Market by Country
10.3.5.2 Asia Pacific Government & Public Sector Market by Country
10.3.5.3 Asia Pacific Automotive, Transportation & Logistics Market by Country
10.3.5.4 Asia Pacific Healthcare & Lifesciences Market by Country
10.3.5.5 Asia Pacific Media & Entertainment Market by Country
10.3.5.6 Asia Pacific Manufacturing Market by Country
10.3.5.7 Asia Pacific Retail & eCommerce Market by Country
10.3.5.8 Asia Pacific Telecommunications Market by Country
10.3.5.9 Asia Pacific Others Market by Country
10.3.6 Asia Pacific Multimodal AI Market by Country
10.3.6.1 China Multimodal AI Market
10.3.6.1.1 China Multimodal AI Market by Offering
10.3.6.1.2 China Multimodal AI Market by Type
10.3.6.1.3 China Multimodal AI Market by Technology
10.3.6.1.4 China Multimodal AI Market by Data Modality
10.3.6.1.5 China Multimodal AI Market by Vertical
10.3.6.2 Japan Multimodal AI Market
10.3.6.2.1 Japan Multimodal AI Market by Offering
10.3.6.2.2 Japan Multimodal AI Market by Type
10.3.6.2.3 Japan Multimodal AI Market by Technology
10.3.6.2.4 Japan Multimodal AI Market by Data Modality
10.3.6.2.5 Japan Multimodal AI Market by Vertical
10.3.6.3 India Multimodal AI Market
10.3.6.3.1 India Multimodal AI Market by Offering
10.3.6.3.2 India Multimodal AI Market by Type
10.3.6.3.3 India Multimodal AI Market by Technology
10.3.6.3.4 India Multimodal AI Market by Data Modality
10.3.6.3.5 India Multimodal AI Market by Vertical
10.3.6.4 South Korea Multimodal AI Market
10.3.6.4.1 South Korea Multimodal AI Market by Offering
10.3.6.4.2 South Korea Multimodal AI Market by Type
10.3.6.4.3 South Korea Multimodal AI Market by Technology
10.3.6.4.4 South Korea Multimodal AI Market by Data Modality
10.3.6.4.5 South Korea Multimodal AI Market by Vertical
10.3.6.5 Singapore Multimodal AI Market
10.3.6.5.1 Singapore Multimodal AI Market by Offering
10.3.6.5.2 Singapore Multimodal AI Market by Type
10.3.6.5.3 Singapore Multimodal AI Market by Technology
10.3.6.5.4 Singapore Multimodal AI Market by Data Modality
10.3.6.5.5 Singapore Multimodal AI Market by Vertical
10.3.6.6 Malaysia Multimodal AI Market
10.3.6.6.1 Malaysia Multimodal AI Market by Offering
10.3.6.6.2 Malaysia Multimodal AI Market by Type
10.3.6.6.3 Malaysia Multimodal AI Market by Technology
10.3.6.6.4 Malaysia Multimodal AI Market by Data Modality
10.3.6.6.5 Malaysia Multimodal AI Market by Vertical
10.3.6.7 Rest of Asia Pacific Multimodal AI Market
10.3.6.7.1 Rest of Asia Pacific Multimodal AI Market by Offering
10.3.6.7.2 Rest of Asia Pacific Multimodal AI Market by Type
10.3.6.7.3 Rest of Asia Pacific Multimodal AI Market by Technology
10.3.6.7.4 Rest of Asia Pacific Multimodal AI Market by Data Modality
10.3.6.7.5 Rest of Asia Pacific Multimodal AI Market by Vertical
10.4 LAMEA Multimodal AI Market
10.4.1 LAMEA Multimodal AI Market by Offering
10.4.1.1 LAMEA Solution Market by Country
10.4.1.2 LAMEA Multimodal AI Market by Solution Deployment Type
10.4.1.2.1 LAMEA Cloud Market by Country
10.4.1.2.2 LAMEA On-premise Market by Country
10.4.1.3 LAMEA Multimodal AI Market by Solution Type
10.4.1.3.1 LAMEA Platform Market by Country
10.4.1.3.2 LAMEA Software Market by Country
10.4.1.3.3 LAMEA Framework Market by Country
10.4.1.4 LAMEA Services Market by Country
10.4.2 LAMEA Multimodal AI Market by Type
10.4.2.1 LAMEA Generative Market by Country
10.4.2.2 LAMEA Translative Market by Country
10.4.2.3 LAMEA Interactive Market by Country
10.4.2.4 LAMEA Explanatory Market by Country
10.4.3 LAMEA Multimodal AI Market by Technology
10.4.3.1 LAMEA Natural Language Processing Market by Country
10.4.3.2 LAMEA Machine Learning Market by Country
10.4.3.3 LAMEA Computer Vision Market by Country
10.4.3.4 LAMEA Context Awareness Market by Country
10.4.3.5 LAMEA Internet of Things Market by Country
10.4.4 LAMEA Multimodal AI Market by Data Modality
10.4.4.1 LAMEA Image Data Market by Country
10.4.4.2 LAMEA Video Data Market by Country
10.4.4.3 LAMEA Text Data Market by Country
10.4.4.4 LAMEA Speech & Voice Data Market by Country
10.4.4.5 LAMEA Audio Data Market by Country
10.4.5 LAMEA Multimodal AI Market by Vertical
10.4.5.1 LAMEA BFSI Market by Country
10.4.5.2 LAMEA Government & Public Sector Market by Country
10.4.5.3 LAMEA Automotive, Transportation & Logistics Market by Country
10.4.5.4 LAMEA Healthcare & Lifesciences Market by Country
10.4.5.5 LAMEA Media & Entertainment Market by Country
10.4.5.6 LAMEA Manufacturing Market by Country
10.4.5.7 LAMEA Retail & eCommerce Market by Country
10.4.5.8 LAMEA Telecommunications Market by Country
10.4.5.9 LAMEA Others Market by Country
10.4.6 LAMEA Multimodal AI Market by Country
10.4.6.1 Brazil Multimodal AI Market
10.4.6.1.1 Brazil Multimodal AI Market by Offering
10.4.6.1.2 Brazil Multimodal AI Market by Type
10.4.6.1.3 Brazil Multimodal AI Market by Technology
10.4.6.1.4 Brazil Multimodal AI Market by Data Modality
10.4.6.1.5 Brazil Multimodal AI Market by Vertical
10.4.6.2 Argentina Multimodal AI Market
10.4.6.2.1 Argentina Multimodal AI Market by Offering
10.4.6.2.2 Argentina Multimodal AI Market by Type
10.4.6.2.3 Argentina Multimodal AI Market by Technology
10.4.6.2.4 Argentina Multimodal AI Market by Data Modality
10.4.6.2.5 Argentina Multimodal AI Market by Vertical
10.4.6.3 UAE Multimodal AI Market
10.4.6.3.1 UAE Multimodal AI Market by Offering
10.4.6.3.2 UAE Multimodal AI Market by Type
10.4.6.3.3 UAE Multimodal AI Market by Technology
10.4.6.3.4 UAE Multimodal AI Market by Data Modality
10.4.6.3.5 UAE Multimodal AI Market by Vertical
10.4.6.4 Saudi Arabia Multimodal AI Market
10.4.6.4.1 Saudi Arabia Multimodal AI Market by Offering
10.4.6.4.2 Saudi Arabia Multimodal AI Market by Type
10.4.6.4.3 Saudi Arabia Multimodal AI Market by Technology
10.4.6.4.4 Saudi Arabia Multimodal AI Market by Data Modality
10.4.6.4.5 Saudi Arabia Multimodal AI Market by Vertical
10.4.6.5 South Africa Multimodal AI Market
10.4.6.5.1 South Africa Multimodal AI Market by Offering
10.4.6.5.2 South Africa Multimodal AI Market by Type
10.4.6.5.3 South Africa Multimodal AI Market by Technology
10.4.6.5.4 South Africa Multimodal AI Market by Data Modality
10.4.6.5.5 South Africa Multimodal AI Market by Vertical
10.4.6.6 Nigeria Multimodal AI Market
10.4.6.6.1 Nigeria Multimodal AI Market by Offering
10.4.6.6.2 Nigeria Multimodal AI Market by Type
10.4.6.6.3 Nigeria Multimodal AI Market by Technology
10.4.6.6.4 Nigeria Multimodal AI Market by Data Modality
10.4.6.6.5 Nigeria Multimodal AI Market by Vertical
10.4.6.7 Rest of LAMEA Multimodal AI Market
10.4.6.7.1 Rest of LAMEA Multimodal AI Market by Offering
10.4.6.7.2 Rest of LAMEA Multimodal AI Market by Type
10.4.6.7.3 Rest of LAMEA Multimodal AI Market by Technology
10.4.6.7.4 Rest of LAMEA Multimodal AI Market by Data Modality
10.4.6.7.5 Rest of LAMEA Multimodal AI Market by Vertical
Chapter 11. Company Profiles
11.1 Twelve Labs Inc.
11.1.1 Company Overview
11.2 Aimesoft
11.2.1 Company Overview
11.2.2 Recent strategies and developments:
11.2.2.1 Product Launches and Product Expansions:
11.2.2.2 Geographical Expansions:
11.3 Jina AI GmbH
11.3.1 Company Overview
11.4 Uniphore Technologies Inc.
11.4.1 Company Overview
11.4.2 Recent strategies and developments:
11.4.2.1 Partnerships, Collaborations, and Agreements:
11.4.2.2 Acquisition and Mergers:
11.5 Google LLC (Alphabet Inc.)
11.5.1 Company Overview
11.5.2 Financial Analysis
11.5.3 Segmental and Regional Analysis
11.5.4 Research & Development Expense
11.5.5 Recent strategies and developments:
11.5.5.1 Partnerships, Collaborations, and Agreements:
11.5.5.2 Product Launches and Product Expansions:
11.5.6 SWOT Analysis
11.6 Microsoft Corporation
11.6.1 Company Overview
11.6.2 Financial Analysis
11.6.3 Segmental and Regional Analysis
11.6.4 Research & Development Expenses
11.6.5 Recent strategies and developments:
11.6.5.1 Partnerships, Collaborations, and Agreements:
11.6.5.2 Product Launches and Product Expansions:
11.6.6 SWOT Analysis
11.7 OpenAI, L.L.C.
11.7.1 Company Overview
11.7.2 Recent strategies and developments:
11.7.2.1 Partnerships, Collaborations, and Agreements:
11.7.3 SWOT Analysis
11.8 Meta Platforms, Inc. (Meta)
11.8.1 Company Overview
11.8.2 Financial Analysis
11.8.3 Segment and Regional Analysis
11.8.4 Research & Development Expense
11.8.5 Recent strategies and developments:
11.8.5.1 Partnerships, Collaborations, and Agreements:
11.8.5.2 Product Launches and Product Expansions:
11.8.6 SWOT Analysis
11.9 Amazon Web Services, Inc. (Amazon.com, Inc.)
11.9.1 Company Overview
11.9.2 Financial Analysis
11.9.3 Segmental Analysis
11.9.4 Recent strategies and developments:
11.9.4.1 Partnerships, Collaborations, and Agreements:
11.9.4.2 Product Launches and Product Expansions:
11.9.5 SWOT Analysis
11.10. IBM Corporation
11.10.1 Company Overview
11.10.2 Financial Analysis
11.10.3 Regional & Segmental Analysis
11.10.4 Research & Development Expenses
11.10.5 Recent strategies and developments:
11.10.5.1 Partnerships, Collaborations, and Agreements:
11.10.5.2 Product Launches and Product Expansions:
11.10.6 SWOT Analysis
Chapter 12. Winning Strategies of Multimodal AI Market

Download our eBook: How to Succeed Using Market Research

Learn how to effectively navigate the market research process to help guide your organization on the journey to success.

Download eBook
Cookie Settings