This article provides an overview of AI software products worth checking out in 2024. This includes various products related to different aspects of AI, including but not limited to tools and platforms for deep learning, computer vision, natural language processing, machine learning, cloud computing, and edge AI.
Hence, the list includes AI software for innovation teams and the best AI platforms for developers and data scientists looking to adopt new, emerging technology for innovation projects.
After providing a list of the most powerful and popular AI software products for enterprise and business applications, we will provide a comprehensive overview of the latest technology trends that drive AI adoption today.
In this article, we will cover the following topics:
- List of the best AI software products and platforms
- Comparison, overview, and pricing of AI software alternatives
- The most important, new trends in AI software for enterprise
What is AI Software
AI software is a type of computer software that enables the adoption of Artificial Intelligence (AI) to process large amounts of data to solve tasks that otherwise require human intelligence. Such tasks include image recognition, video analytics, generative AI, voice recognition, text recognition, and NLP.
The strategic importance of AI technology is growing exponentially across industries. Many businesses are exploring and investing in AI solutions to stay competitive and enhance their business processes. Late movers are at risk of falling behind their competitors in terms of technological adoption and innovation.
This is because AI has the ability to automate tasks and processes that would otherwise not be possible or carried out by humans. As a result, businesses that don’t adopt AI will lose out on cost efficiencies, productivity advantages, and product or customer service quality.
The Top AI Software in 2024
- Software #1: Viso Suite Platform
- Software #2: ChatGPT Software
- Software #3: Jupyter Notebooks
- Software #4: Google Cloud AI Platform
- Software #5: Azure Machine Learning Studio
- Software #6: Infosys Nia
- Software #7: Salesforce Einstein
- Software #8: Chorus.ai
- Software #9: Observe.AI
- Software #10: TensorFlow
- Software #11: H2O.ai
- Software #12: C3 AI
- Software #13: IBM Watson
- Software #14: DataRobot
- Software #15: Tractable
- Software #16: Content DNA Platform
- Software #17: Synthesia
1. Viso Suite Platform
Viso Suite is the world’s only end-to-end computer vision application platform. The solution provides a scalable software infrastructure to develop, deploy, scale, and secure AI vision applications (Get the Whitepaper).
Some of the largest companies in the world use the Viso platform to deliver and maintain their portfolio of computer vision applications. Find case studies, AI projects, and industry solutions here.
Viso Suite lets you unify infrastructure for all computer vision projects, to avoid purchasing and integrating point solutions for each project. The platform integrates enterprise AI products for the entire lifecycle: Data collection, image annotation, model training, application development, deployment, configuration, and monitoring (see all features).
The Viso platform provides revolutionary no-code and low-code tools. The visual programming follows a modular “build once – deploy anywhere” approach with a powerful drag-and-drop interface. Teams can rapidly build custom applications, integrate existing cameras, and always use the latest algorithms (e.g., YOLOv7).
Viso Suite enables organizations to solve the challenges of scaling computer vision. It provides the device management, privacy/security capabilities, remote monitoring, and configuration management needed to operate AI vision at a large scale.
- To evaluate Viso Suite for your organization, request a demo here.
- There are different Viso Suite Editions – with unlimited users, camera streams, and computer vision applications included.
- And there are service packages, from on-demand assistance to full Computer-Vision-as-a-Service.
ChatGPT is a large language model chatbot developed by OpenAI that is able to interact in conversational dialogue form and provide responses that can appear surprisingly human (read more about Natural Language Processing, NLP). It was trained on massive amounts of data about code and information from the internet, including sources like Reddit discussions, to help ChatGPT learn dialogue and attain a human style of responding. Additionally, ChatGPT was trained using human feedback, a technique called Reinforcement Learning with Human Feedback, so that the AI learned what humans expected when they asked a question
ChatGPT is a hugely successful tool, with over one million users only weeks after launch. However, major companies such as JPMorgan Chase, Amazon, Verizon, and Accenture have barred staff from using the AI chatbot; some even blocked it entirely. An important limitation is that because ChatGPT is trained to provide answers that feel right to humans, the answers can trick humans that the output is correct. Hence, the responses may be factually wrong and deceiving. Moreover, some organizations are concerned that employees may share sensitive or confidential information.
The ChatGPT tool can be used for free; you can start here. In January 2023, OpenAI added a paid version that responds faster and keeps working even during peak usage times. In November 2023, the company introduced GPTs for users to customize ChatGPT for a specific purpose. There will also be a GPT Store to find and share GPTs publicly. Enterprise customers can now deploy internal-only GPTs for highly customized tasks such as customer support, internal training bots, etc.
OpenAI has announced a subscription service for ChatGPT, the conversational AI chatbot that answers follow-up questions and challenges assumptions. As of the end of 2023, The ChatGPT Plus service costs $20 per month and offers faster response times, general access to ChatGPT, and priority access to new features and improvements.
For developers, GPT-4 Turbo is an API service to integrate language models of OpenAI with custom software. There are different models, each with different capabilities and price points. Prices are per 1,000 tokens, where tokens act like pieces of words, where 1,000 equals about 750 words. The unit of 1,000 tokens costs between $0.03 for text input to $0.12 for text output tasks.
3. Jupyter Notebooks
Jupyter notebooks are a powerful open-source software tool for code-first users to write and run computer code. The name “Jupyter” is a reference to the three core programming languages supported by Jupyter: Julia, Python, and R.
Notebooks are easy to use: you can run code cells and see the output without having to write any extra code. Hence, Jupyter Notebooks are popularly used for AI applications, data exploration, prototyping algorithms, vision pipelines, and developing machine learning models across the enterprise.
As one of the most popular AI software, notebooks enable organizations to establish a unified environment that provides a powerful and code-first experience for data scientists. This is important because most data scientists collaborate in teams of 10 or more specialists, each with their own preference and expertise in tools and frameworks.
In January 2023, the Jupyter extension for Visual Studio Code was downloaded more than 53 Mio times, making it the second-most popular extension in the VS Code Marketplace.
The largest cloud computing providers use Jupyter Notebook or a modified variant as a frontend interface as part of their products, such as Amazon SageMaker Notebooks, Microsoft Azure Notebook, or the Google Colaboratory (Google Colab Notebooks). Other ML software platforms, such as DataRobot, offer integrated and pre-built notebooks.
The computer vision platform Viso Suite provides notebooks for end-to-end model training automation.
4. Google Cloud AI Platform
With Google Cloud AI, you get a set of different machine learning tools. For companies that decided to build their platform on Google Cloud (GCP), it is a popular platform for scientists and developers. The AI software tools of Google Cloud allow developers to work on machine learning projects in a time-saving and cost-effective way.
You can access various pre-trained cloud APIs to build ML applications related to computer vision, translation, natural language, video, etc. Google Cloud supports almost all commonly supported open-source frameworks, including PyTorch, TensorFlow, and scikit-learn.
Update: Google Cloud is shutting down its IoT platform, limiting Edge AI/Edge ML capabilities. As of August 15, 2023, Google Cloud IoT Core service will no longer be available. This means that users will not be able to access the Device Manager API’s.
The Google Cloud platform provides a free trial for new users, post which you have to pay an hourly rate that varies according to the region and operation you choose.
5. Azure Machine Learning Studio
The Azure Machine Learning Studio allows you to create and deploy robust ML models easily to the Azure Cloud with the help of several available tools. It supports several open-source frameworks and languages, including TensorFlow, PyTorch, Python, R, and others.
The Microsoft AI software platform is suitable for a range of users with different skill levels, including developers and scientists. If you decide to stay on Microsoft Azure, the ML studio is a great option to evaluate.
You need to create a free account on the platform to access the features. While a set of services is free to start, some services require a subscription-based account upgrade.
6. Infosys Nia
Infosys Nia is an AI software platform designed to simplify the AI implementation process for businesses and enterprises. It is useful for various tasks related to machine learning, deep learning, data management, Natural Language Processing (NLP), etc.
Infosys Nia provides companies with the opportunity to leverage AI on existing big data, by automating repetitive tasks and scheduled responsibilities. This allows organizations to be more productive and allows workers to be more efficacious in conducting their tasks.
The pricing is available upon request, and it does not come with a free trial.
7. Salesforce Einstein
Salesforce Einstein is an analytics AI platform for CRM (Customer Relationship Management) that businesses can build AI-powered applications for their customers or employees. It allows you to build predictive models related to machine learning, natural language processing, and computer vision. The artificial intelligence tools do not require any model management or data preparation.
There are several pricing packages starting from $25 per user and month, depending on the business requirements. The pricing details are available on the official website. It also provides a free trial for all new users.
Chorus.ai is a conversation intelligence platform designed specifically for high-growth sales teams. It helps you record, manage, and transcribe your calls in real time while also allowing you to mark important action items and topics within the duration.
This AI software allows you to gain highly valuable insights by analyzing your data. Such automation tools make it easier for sales teams to streamline and organize their communication process and engage in errorless follow-ups. Some of its features include call recording, sales coaching, sales management, etc.
There are no public pricing details available; it is custom upon request.
Observe.AI is a call-analysis platform that allows businesses to transcribe calls and use automated speech recognition to improve performance in real-time. The automation tools are user-friendly and support both English and Spanish languages.
It enables businesses and organizations to analyze calls using the most up-to-date speech and natural language processing technologies effectively. The tool can be integrated with other business intelligence software.
You can schedule a demo with an Observe.AI solution architect to learn more about the platform. Pricing details can be availed by reaching out to the team directly. They do not offer any free trial.
10. TensorFlow 2.0
TensorFlow (TF) is a python-based open-source end-to-end numerical computation and machine learning platform for developers to build large-scale multi-layered neural network-based models. TensorFlow was created by Google and is one of the most popular artificial intelligence software with a wide range of deep learning capabilities.
Therefore, numerous enterprise-grade platforms integrate TensorFlow and add additional functionality to facilitate deployment and third-party system integration. For example, the computer vision platform Viso Suite provides a no-code interface to create AI vision applications with TensorFlow that can scale to thousands of edge devices and cameras.
The TensorFlow platform allows you to conveniently build and deploy AI-based applications in the cloud, at the edge, on-premise, on iOS and Android devices, or in a browser. It is useful for various tasks in image recognition, AI video analytics and detection, time series, voice recognition, etc.
This AI software library is free to use and comes with great community support. It is suitable for both beginners and experts, although it comes with a steep learning curve.
H2O.ai is an end-to-end platform designed to help businesses train ML models and applications with remarkable ease. It allows both beginners and experts to build or train AI models by leveraging AutoML functionalities.
The platform supports multiple forms of data, including tabular, text, image, audio, and video. The open-source machine learning solution for enterprises helps businesses manage digital advertising, claims management, fraud detection, advanced analytics, building a virtual assistant, and more.
You can opt for a free trial that allows you full access to the platform for a period of 14 days. From public list prices, we can see that the H2O Driverless AI subscription starts at $300,000.
12. C3 AI
C3 AI, or C3.ai, is an enterprise artificial intelligence software company that provides AI software-as-a-service (Saas) for building AI applications and accelerating digital transformation. C3.ai offers two families of software solutions for AI: C3 AI Suite and C3 AI applications.
The AI platform company provides applications for multiple languages and commercial uses, including energy management, predictive maintenance, fraud detection, anti-money laundering, inventory optimization, and predictive CRM.
The company doesn’t disclose the pricing of the C3 AI products, and it’s suitable for enterprises with large budgets.
13. IBM Watson
The IBM Watson platform allows businesses and organizations to automate complex machine learning processes, predict future outcomes, and optimize their employees’ time. IBM offers a broad AI portfolio with pre-trained models or the option to train a custom machine learning model to make sense of data, pattern recognition, and make predictions.
Update: As of December 1st, 2023, IBM discontinued its IoT Platform Service from IBM Watson. This means that third-party software products/services will be required for deployment, connectivity, and Edge AI.
You can get started with a free demo that gives you limited access to the platform’s features. The professional edition is $80 per user monthly ($960/year per user). The detailed pricing requires a custom quote.
DataRobot is an automated machine learning platform that helps organizations accelerate the development of predictive models and uncover insights from data analysis. It is designed for data scientists, developers, and business analysts who want to build and deploy high-quality machine learning models quickly and efficiently.
The cost of DataRobot varies depending on the plan that you choose, with options ranging from an individual subscription to enterprise options.
In the AWS marketplace, DataRobot AI Cloud starts from $98,000 USD, with a starter pack from AutoML, AutoTS, MLOps, 5 users, and standard support.
Tractable is an AI-driven platform meant to empower automotive, industrial, and insurance industries by providing automated and efficient solutions for accident assessment. It helps with reducing the hassle of manually assessing damaged vehicles, accelerating the workflow of claims processing, and streamlining operations.
Built with a focus on accuracy, Tractable utilizes computer vision powered by deep learning to detect and accurately estimate the cost of repairing a vehicle. Its AI algorithms are trained on millions of images from previous accidents, which enables it to rapidly process and analyze any damage to cars in seconds, producing an accurate assessment of repair costs.
16. Content DNA Platform
Content DNA is an artificial intelligence software platform that specializes in video content analysis. Broadcasters and telecom companies use the product to perform various video-related tasks, including scene recognition, anomaly detection, and enriching metadata. The platform is easy to learn and use, even if you aren’t a specialized professional.
You can access all the features of this AI software free of cost for a limited period (up to 100 hours of processing). You need to pay a one-time setup fee that covers maintenance and cloud infrastructure if you want unlimited access. The pricing requires an individual quote.
Synthesia is an emerging leader in the AI-driven avatar industry. The company is providing a software platform for video content creation through advanced synthetic video technology. Through the use of generative AI, their technology transforms physical video production into an entirely digital process, saving up to 80% of the time and budget to create videos at scale.
Use cases include training videos for sales or technical training, customer service, and marketing. There is a large number of AI avatars available, with over 120 AI voices and ready-to-use video templates.
Synthesias product is priced starting from $265 per year, or $804 for the professional plan. There are enterprise options that provide access to advanced features and the ability to create more videos.
Trends in Business and Enterprise AI Software
AI Technology Trends
AI is driven by the convergence of key emerging technology vectors, namely Cloud Computing, Big Data, Artificial Intelligence, and the Internet of Things (IoT or AIoT). Hence, it is now becoming possible to solve problems previously deemed unsolvable at massive scales.
Notably, Edge Computing is a distributed computing paradigm that brings enterprise applications closer to data sources such as IoT or Edge Devices. The concept that leverages those technologies in combination is called Edge AI, or Edge Intelligence.
Edge AI makes it possible to process big data generated by connected IoT devices at the network edge, using machine learning and deep learning. By moving workloads from the cloud to the network edge closer to where data is generated, it becomes now possible to build highly efficient, connected, robust, and scalable system architectures with powerful AI features. Check out our guide about the cost of computer vision to learn about the immense impact of software architectures (Cloud vs. Edge) on cost.
AI Platforms and new development technologies
Enterprise AI becomes possible thanks to platforms that bring together all infrastructure, microservices, data sources, and research. By using scalable platforms that offer automation, no-code/low-code environments, and manage integration with hardware and software, businesses can adopt AI technology while greatly improving the productivity of the development team by a factor of 10-100x.
AI software for PC and on-premise deployments is increasingly replaced by cloud AI software that provides tools and fully managed AI programs that can be accessed directly via browser. Such solutions do not require users to install a software client, hence enabling a dramatically better user experience and collaboration. Hence, users are not required to download sensitive training data or even models to their local machine.
Enterprise AI applications
There is a rapidly growing number of enterprise use cases, and most organizations have implemented a broad AI strategy to keep up with disruptive technologies. AI applications such as predictive maintenance, fraud detection, smart sensing, supply chain monitoring, energy management, inspection automation, anti-money laundering, and in-store retail analytics are among the problems that are now solvable at the enterprise scale.
Popular enterprise AI applications include solving predictive maintenance problems, monitoring oil and gas assets, predictive cooking in restaurants, inventory optimization in logistics, industrial automation in manufacturing, fraud detection in insurance, animal monitoring in agriculture, and many more.
If you are looking to build computer vision and evaluate enterprise AI software platforms, please get in touch. We are happy to provide you with additional information to help with the evaluation process to find the best AI program or platform for your use case.
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