The transportation sector is using artificial intelligence platform and ML technology to solve problems related to traffic congestion. AI capabilities such as ML are embedded in video surveillance to detect traffic anomalies. The algorithms are highly useful to determine traffic flow, road congestions, accidents on the road, and so on. Due to these benefits, algorithms are proving beneficial in saving the valuable human time required to analyze the traffic. Moreover, algorithms are used in transportation and logistics planning to achieve efficiency and effectiveness in the process. Apart from that, AI capabilities such as speech recognition and vision are also used in the transportation sector. Moreover, another technological capability such as AI and robotics are important elements in autonomous driving and sensors that generate a large amount of data. To analyze that data, ML technology is used.

Artificial Intelligence Platform in Transportation and Logistics Quadrant

Comparing 26 vendors in Artificial Intelligence Platform across 232 criteria.

Find the best Artificial Intelligence Platform solution for your business, using ratings and reviews from buyers, analysts, vendors and industry experts

EVALUATION CRITERIA

Below criteria are most commonly used for comparing Artificial Intelligence Platform tools.
  • Product Features and Functionality
    • Features Offered
      • Natural Language Processing
      • Machine Learning
      • Chatbots or Robots
      • Speech Recognition
      • Text Recognition
      • Forecasts and Prescriptive Models
  • Focus on Product Innovation
    • No. of Innovations
    • R&D Spend
    • Product Enhancement Development
      • Product Upgradation
      • New Product Launches
  • Breadth and Depth of Product Offering
  • Product Branding
    • Customer testimonials
    • Brand Recognition
    • Product Branding
      • Enhance Customer base
      • Increase Revenue
      • Enhance year on year growth
      • Sustain in competition
      • Other Branding Method(s)
    • No. of Platforms for Branding
      • Social Media Platforms
      • Mobile Apps
      • Offlne campaigns
      • Word of Mouth strategy
      • Email Branding
      • Articles and Blogs
      • Other Branding Platform(s)
  • Support Services
    • Services
      • Managed Services
      • Professional Services
    • Support
      • Sales Support
      • Technical Support
      • Customer Support
      • Other Support Services
  • End-Users served
    • Large Enterprises (Revenue> 500 Million)
    • Small Enterprise (Revenue< 100 Million)
    • Medium Enterprises (100 Million<Revenue<500 Million)
  • Deployment Mode
    • Cloud
    • On-Premise
  • Delivery Model
    • Per User Basis
    • Subscription / Licensing
    • Full Time Equivalent

TOP VENDORS (23)

  • 1

    Microsoft offers AI platform services and tools to help developers in creating AI-enabled models. Moreover, it is said to be heavily investing in services, tools, and platforms to help bring AI and data-driven intelligence into every application. Apart from that, the company launched new tools and services, such as Azure data and cloud services, to help developers in modernizing applications. Additionally, the company’s focus areas for investment include intelligent edge and intelligent cloud. It also opened the Microsoft Research AI lab, which focuses on solving hurdles in the AI space. The technologies involved in the research are ML, NLP, decision-making, and visual perception.

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    • Enterprise
    • Washington, USA
    • Founded: 1975
    • More than $100 BN
    • 1,00,001 to 5,00,000
  • 2

    Google Cloud Platform offers cloud computing services that comprise ML, data analytics, and data storage capabilities. The platform provides features, such as secure and cost-effective infrastructure, along with data and analytics capabilities, for better product development. Moreover, Google offers the open source library, TensorFlow, to carry out numerical calculations with the help of data flow graphs. TensorFlow helps users from various industry backgrounds in using different applications, ranging from language translation to early detection of diseases. Apart from that, Google’s ML Engine enables developers to create ML models on any size of data. Additionally, its Cloud Machine Learning Engine offers managed services that negate the need for infrastructure and provide the basis for model development and prediction. It also adds portability, flexibility, and the ease of use. Additionally, Google’s Cloud Video Intelligence API is designed to concentrate on video analytics for the new audience. Furthermore, the Cloud Video Intelligence API makes the video searching process easier.

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    • Enterprise
    • California, US
    • Founded: 1998
    • More than $100 BN
    • 75,001 to 1,00,000
  • 3

    IBM Watson suite enables organizations to combine AI into their applications, and also helps with data management in the cloud. It offers the PowerAI platform, which provides various AI capabilities. These capabilities negate the need for developing AI solutions. Moreover, the PowerAI platform provides AI-rich capabilities, such as deep learning, which allows organizations to fulfill the technological requirements. The IBM Power Systems software combined with the PowerAI platform allows enterprises to deploy PowerAI with deep learning capabilities for enhanced performance.

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    • Enterprise
    • New York, USA
    • Founded: 1911
    • $50BN to $100BN
    • 1,00,001 to 5,00,000
  • 4

    AWS Managed ML Platforms offers data scientists and developers a way to create models without investing in infrastructure management. Amazon ML removes the need to learn complex technologies and ML algorithms, along with visualization tools and wizards to help guide in the process of building ML models. Apache Spark on Amazon EMR is an open source distributed processing system, which focuses on big data workloads. It offers various features, such as enhancing the performance and enabling the quick development of applications, such as libraries, to help develop applications for various uses cases. Amazon Web Services also offers intelligent services to build application, such as Amazon Lex, Amazon Polly, and Amazon Rekognition. The services are used to turn text into speech, as well as, help study the images to recognize faces, objects, and scenes.

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    • Enterprise
    • Washington, USA
    • Founded: 1994
    • More than $100 BN
    • 5,00,001 & more
  • 5

    SAP Leonardo Machine Learning platform is created on SAP Cloud Platform and comprises the capabilities of ML to help organizations in finding connections and patterns in the data. It comprises services that offer the capabilities to learn from data as well as gain knowledge. Moreover, it allows taking advantage of the intelligent capabilities for developing enterprise applications and removes the need for data science skills in the process. The SAP Leonardo ML platform offers the basis to create and manage intelligent applications under a common infrastructure. Moreover, SAP offers SAP CoPilot, the virtual assistant designed to help customers. The virtual assistant analyzes the unstructured speech to offer users with relevant data.

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    • Enterprise
    • Weinheim, Germany
    • Founded: 1972
    • $10BN to $50BN
    • 75,001 to 1,00,000
  • 6

    Intel has adopted the acquisitions strategy to strengthen its Artificial Intelligence Platform platform offerings; for instance, it acquired Nervana Systems, an expert in ML capabilities. Apart from the acquisition’s strategy, the company is also said to be making capital investments to accelerate the AI innovation in companies, such as AEye, Element AI, and CognitiveScale. Moreover, the company has made investments in startups to enhance its AI platform’s technological capabilities. Apart from acquisitions and investments, the company formed a partnership with Tata Consultancy Services to build the architecture for AI, IoT, cloud, and 5G. With such strategies, Intel is trying to sustain in a competitive position in the AI platform technologies, such as deep learning, neural networks, and ML. Moreover, to enhance its product offerings, the company focuses on the upcoming Intel Nervana ASIC (Application-Specific Integrated Circuit) engine, designed to enhance the deep learning capabilities of neural networks. Moreover, the engine helps in speeding up the process of AI training.

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    • Enterprise
    • California, USA
    • Founded: 1968
    • $50BN to $100BN
    • 1,00,001 to 5,00,000
  • 7

    Salesforce Einstein suite offers data modeling, preparation, and infrastructure processes, which can be embedded into predictive models and applications to benefit from capabilities. The Einstein platform services offer the basis to create AI-driven applications by making available, the capabilities of image recognition and NLP to the users. The Marketing Cloud Einstein allows the marketers to take benefits of tools, such as Predictive Scoring, Predictive Audiences, and Automated Send-time Optimization, to analyze the target audience, contents, and channels while designing campaigns. Furthermore, the Analytics Cloud Einstein helps in the discovery of future patterns for business processes and provides insights from a large chunk of data. These platforms remove the need to build algorithms and mathematical models. Moreover, by using Service Cloud Einstein, enterprises can achieve intelligent, automated, and predictive customer engagement experience. The Community Cloud Einstein offers customers a way to find the information and offers recommendations about the contents.

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    • Enterprise
    • California, US
    • Founded: 1999
    • $5BN to $10BN
    • 30,001 to 35,000
  • 8

    Qualcomm has been focusing on bringing ML and AI technologies to various industrial applications. For instance, to enhance the capabilities of the Artificial Intelligence Platform technology across various industries, such as manufacturing and finance, the company acquired Scyfer B.V., which possesses developed capabilities in ML. Qualcomm also helps bring AI-enabled applications to various industries. Qualcomm has raised a funding of USD 14 million, under Series C, for its BrainOS platform. The platform is a software built with the help of sensors and hardware, designed to offer a basis for creating autonomous robots. Apart from this, the company is working on building AI technologies in various devices, such as robots and cars, to negate the requirement of network or Wi-Fi. Additionally, the company’s consistent efforts in R&D in AI is evident from the fact that it started the Qualcomm Research in the Netherlands in 2014, as well as, acquired Euvision Technologies. Moreover, in 2016, it collaborated with Google to speed up TensorFlow, Google’s open source library. Qualcomm, with the help from the University of Amsterdam, created a research lab. Additionally, in 2017, the company announced its support for deep learning frameworks, such as Caffe2 and TensorFlow.

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    • Enterprise
    • California, USA
    • Founded: 1985
    • $10BN to $50BN
    • 30,001 to 35,000
  • 9

    The company focuses on the launch of AI-enabled platforms, which is evident from the fact that, HPE unveiled a software solution, Investigate Analytics, which comprises big data and AI technologies, designed to help the financial firms with identifying risk and fraudulent behaviors. This offering was launched at the LegalTech conference in New York City to help identify such frauds and risks by analyzing large amounts of data. Moreover, the company launched hardware, services, and software in June 2017, which were designed to deliver high-performance computing and AI technologies. These hardware, services, and software also help scientific institutes and organizations in gaining insights into large amounts of data. Additionally, these solutions focus on helping organizations with the security and cost factors. HPE partnered with BASF SE. As a part of this partnership, HPE would help BASF SE develop supercomputers. HPE’s Apollo system would assist in creating and developing the modeling and simulation approach, so that BASF SE can find new opportunities in the process of simulation and complex modeling development during its research process.

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    • Enterprise
    • California, USA
    • Founded: 2015
    • $10BN to $50BN
    • 10,001 to 15,000
  • 10

    SAS Visual Data Mining and Machine Learning offers an innovative solution that combines the most advanced analytics, data prep, visualization, model assessment and model deployment in a single environment. It also supports programming from popular open source languages. This reliable, collective environment produces desired outcomes, helping improve organizational procedures and discover new opportunities for growth.

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    • Enterprise
    • North Carolina, USA
    • Founded: 1976
    • $1BN to $5BN
    • 10,001 to 15,000
  • 11

    The company is focused on adopting the software automation platform, along with AI-based automation techniques, to increase the efficiency of its projects. Infosys’ Mana platform of AI was adopted by many its clients to achieve efficiency and automation. Moreover, the company invested in the Danish AI startup, UNSILO, which leverages NLP and ML to gain insights into numerous texts for increasing the efficiency and the speed of workers. Additionally, to help clients take advantage of the AI-based technologies, Infosys launched the AI platform, Nia.

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    • Enterprise
    • Karnataka, India
    • Founded: 2018
    • $10BN to $50BN
    • 1,00,001 to 5,00,000
  • 12

    The company is focused on the innovation and development of AI platform technologies, which is evident from the fact that it partnered with Tel Aviv University’s (TAU) business engagement center, Ramot, in July 2017. The partnership focused on the research of the continuously developing AI technologies. Moreover, Wipro has made investments through the Horizon Program (intrapreneurship program) to nurture AI platform technologies in the organization. Apart from that, the company is focused on its investment in AI technologies for achieving a differentiation in IT services business. Additionally, it launched the automation service for SAP software to automate the business processes that run on SAP’s Enterprise Resource Planning (ERP) software. The automation service includes the capabilities of Wipro’s AI platform, HOLMES.

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    • Enterprise
    • Karnataka, India
    • Founded: 1945
    • $5BN to $10BN
    • 1,00,001 to 5,00,000
  • 13

    Oracle provides readymade AI cloud applications with intellectual features that drive better business outcomes. It offers a full suite of cloud services to build, deploy, and manage AI-powered solutions. It automate security patching, backups, and improve database query performance, which eliminate human error and repetitive manual tasks. so organizations can focus on higher-value activities.

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    • Enterprise
    • California, USA
    • Founded: 1977
    • $10BN to $50BN
    • 1,00,001 to 5,00,000
  • 14

    Ayasdi introduced its AI platform in the healthcare and financial sectors by partnering with Deloitte. Both the companies worked to increase the adoption of AI across various enterprises. Additionally, Ayasdi benefits from Deloitte’s capabilities in cognitive as well as the other emerging technologies for discovering business applications. Moreover, Ayasdi is said to be experiencing a rapid growth in its healthcare vertical, and to cater to the growing demand, the company has made additions to its healthcare staff. The addition of the staff would be useful in increasing the company’s place in key analytical challenges for its solutions, such as patient risk stratification and fraud, clinical variation, and denials management.

    Read More
    • Startup
    • California, US
    • Founded: 2008
    • Below $10 MN
    • 101 to 500
  • 15

    Absolutdata has been updating its product offering in the market; for instance, the company launched the upgraded version NAVIK Converter 2. 0, which comprises technologies, such as advanced analytics and ML, to help brands in designing campaigns. Furthermore, the company launched its AI platform, NAIVIK, as well as, AI-based tools for helping the sales and marketing team in achieving efficiency. Apart from that, to increase its expertise around analytics and achieve a steady growth, the company added more staff. It is believed that the company is attempting to develop more innovative AI platforms to offer better experiences to its clients.

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    • Enterprise
    • Alameda, California, US
    • Founded: 2001
    • 51 to 100
  • 16

    RapidMiner provides a comprehensive solution on a integrated platform that supports the whole Machine Learning workflow from data preparation through model deployment to ongoing model management. It is quick-to-learn and simple-to-use workflow designer accelerates end-to-end data science for improved productivity.

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    • Startup
    • Massachusetts, US
    • Founded: 2006
    • Below $10 MN
    • 51 to 100
  • 17

    DataRobot automated machine learning platform provides knowledge, experience, and best practices to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot allows users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods.

    Read More
    • Startup
    • Massachusetts, US
    • Founded: 2012
    • $10BN to $50BN
    • 101 to 500
  • 18

    The company provides a highly interactive conversational AI betting solution that engages customers over any channel, device, service, and language. It uses linguistic and machine learning techniques for maximum performance on any platform.

    Read More
    • Startup
    • Barcelona, Spain
    • Founded: 2001
    • Below $10 MN
    • 51 to 100
  • 19

    Faculty Platform allows to manage and schedule model training and execution pipelines natively, and deploy models into staging and production with one simple workflow. It use a browser or command line interface that integrates with favourite IDE and version control systems for easy interface customisation.

    Read More
    • Startup
    • London, Westminster
    • Founded: 2014
    • Below $10 MN
    • 1 to 50
  • 20

    Vital AI Development Kit (VDK) offers a suite of software to reorganize the flow of data across application architecture and integrate with analytical frameworks using the Vital Service API. The key tool is VitalSigns, which provides a consistent data model used by all software modules.

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    • Startup
    • New York City, New York, United States
    • Founded: 2011
    • 1 to 50
  • 21

    Msg.ai Artificial Intelligence respond quickly to issues that are repeatable, while enabling human agents to focus on high-impact work. It ensure a best experience to customers whenever there is a  an issue, a question or a need. It can collaborates with human agents to offer high-quality resolutions to customer queries on email, mobile, and chat.      

    Read More
    • Enterprise
    • San Francisco, California
    • Founded: 2015
    • 101 to 500
  • 22

    Rainbird is an AI-powered automated decision-making platform. It goes beyond other rules engines that can only make simple decisions, and limited 'black box' machine learning that can't explain. The platform drives smarter decision-making by enabling semantic links between different Rainbird knowledge maps. It enables to 'join-up' previously siloed knowledge and deliver a more holistic and strategic system, capable of automating complex decisions.

    Read More
    • Enterprise
    • Founded: 2018
    • 501 to 1,000
  • 23

    Figure eight generates high-quality customized training data and automates business process with easy-to-deploy models. It offers products and services like self-driving cars, intelligent personal assistants, medical image labeling, content categorization, customer support ticket classification, social data insight, CRM data enrichment, product categorization, and search relevance.

    Read More
    • SME
    • California, US
    • Founded: 2007
    • $51MN to $100MN
    • 101 to 500

TOP REVIEWS

Looking for Artificial Intelligence Platform? Get help
Internal Analyst,MnM
Internal Analyst, MnM
#21 in Artificial Intelligence Platform

“AI software development tools"

(*)(*)(*)( )( )3
Vital AI provides artificial intelligence software development tools and consulting services to address the source of cost when developing intelligent applications. msg.ai provides a convenient and intelligent way to facilitate the best customer interactions on email, chat, and mobile, to maximize business capacity and ensure high-quality resolutions through AI.
Internal Analyst,MnM
Internal Analyst, MnM
#9 in Artificial Intelligence Platform

“AI-enabled Applications"

(*)(*)( )( )( )2
HPE offers AI platforms and services that aid companies in familiarizing themselves with deep learning technology.
Internal Analyst,MnM
Internal Analyst, MnM
#17 in Artificial Intelligence Platform

“Automated and AI-enabled Applications"

(*)(*)(*)( )( )3
DataRobot provides an ideal combination of automated machine learning, comprehensive training, and professional services to make a vision real.
Internal Analyst,MnM
Internal Analyst, MnM
#7 in Artificial Intelligence Platform

“AI Platform for industrial applications"

(*)(*)(*)(*)( )4
Salesforce offers artificial intelligence services through its platform, Einstein, which provides the basis for creating various industrial applications. The platform offers data modelling, preparation, and infrastructure processes, which can be embedded into predictive models and applications.
Internal Analyst,MnM
Internal Analyst, MnM
#10 in Artificial Intelligence Platform

“Data Science and Machine Learning"

(*)(*)(*)(*)( )4
SAS embeds AI capabilities into business applications to help deliver intelligent, automated solutions that help boost productivity. SAS AI technologies support diverse environments, including machine learning, computer vision, natural language processing, forecasting, and optimization.