This article provides an overview of AI software products worth checking out. For this article, AI software refers to deep learning, computer vision, natural language processing, machine learning, cloud computing, and edge AI tools and platforms.
This list will be of interest to innovation teams, data scientists, and developers in particular—namely, those looking to adopt emerging technology for innovation projects for enterprises in business applications.
Finally, 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?
Artificial Intelligence (AI) software enables businesses to process large amounts of data to solve tasks otherwise requiring human intelligence. Such tasks include image recognition, video analytics, generative AI, voice recognition, text recognition, and Natural Language Processing (NLP).
The strategic importance of AI tools and technology continues to grow rapidly 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.
Without AI, businesses will lose out on cost efficiencies, productivity advantages, and product or customer service quality.
The Top AI Software
- 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
- Software #18: Empower by Ringover
1. Viso Suite AI Software Infrastructure
Viso Suite is the world’s only end-to-end computer vision application infrastructure. The state-of-the-art solution facilitates AI vision application development, deployment, scaling, and securing.
Large enterprises on a global scale use Viso Suite to deliver and maintain their computer vision application portfolios. Find case studies, AI projects, and industry solutions here.
Viso Suite performs all computer vision tasks that are suitable for solving complex business problems. Most notably, Viso Suite unifies infrastructure for all computer vision projects. ML teams can avoid purchasing and integrating point computer vision software solutions for each project. The platform integrates enterprise AI products for the entire lifecycle:
- Data collection
- Data annotation
- Application development
- Model Training
- Deploying to the edge
- IoT connecting
- Analytics monitoring
- Maintenance and debugging
- Securing and protecting
Viso Suite provides visual programming features following a modular “build once deploy anywhere” approach. 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.
2. ChatGPT
ChatGPT is a large language model chatbot developed by OpenAI. It interacts in dialogue form and provides responses that appear surprisingly human. You can learn more about NLP in our blog.
OpenAI trained ChatGPT on massive amounts of data about code and information from the internet. A notable source included Reddit discussions, which helped ChatGPT learn dialogue and attain a human style of responding. Additionally, ChatGPT’s training included a technique called Reinforcement Learning with Human Feedback. This allowed it to learn 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 of ChatGPT is that although its answers can seem “human,” its output is not always correct. Hence, the responses may be factually wrong and deceiving. Moreover, some organizations are concerned that employees may share sensitive or confidential information.
Practical Information
The ChatGPT tool has a free tier. 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 deploy internal-only GPTs for highly customized tasks like customer support and internal training bots.
OpenAI has announced a subscription service for ChatGPT. As of 2023 the subscription costs $20 per month and offers:
- Faster response times
- General access to ChatGPT
- 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 popular for AI applications, data exploration, prototyping algorithms, vision pipelines, and developing machine learning models across the enterprise.
As a popular AI software, notebooks enable organizations to establish a unified environment for a powerful, code-first experience. This is important because most data scientists collaborate in teams of 10 or more specialists. Each member usually has their preference and expertise in tools and deep learning frameworks.
In January 2023, the Jupyter extension for Visual Studio Code had more than 53 million downloads. This made 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 in their products. These include Amazon SageMaker Notebooks, Microsoft Azure Notebook, and the 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.
For personal use or testing, you can find the open-source version of JupyterLab Notebook here.
4. Google Cloud AI Software Platform
With Google Cloud AI, you get a set of different machine learning tools. For companies that built 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 efficiently and cost-effectively on projects.
You can access various pre-trained cloud APIs to build applications for computer vision, translation, natural language, and video. 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. Afterward, you 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. It supports several open-source frameworks and languages, including TensorFlow, PyTorch, Python, R, and others.
The Microsoft AI software platform is suitable for users with varying 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, 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 AI Software
Salesforce Einstein is an analytics platform for Customer Relationship Management for building AI-powered applications. 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.
8. Chorus.ai
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. At the same time, it allows 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 simplify streamlining and organizing communication processes and engage in errorless follow-ups for sales teams. Some of its features include call recording, sales coaching, sales management, etc.
There are no public pricing details available; it is custom upon request.
9. Observe.AI
Observe.AI is a call-analysis platform using automated speech recognition for businesses to improve call performance in real time. The automation tools are user-friendly and support both English and Spanish languages.
Businesses and organizations can analyze calls using the most up-to-date speech and NLP technologies effectively. The tool integrates with other business intelligence software.
You can schedule a demo with an Observe.AI solution architect to learn more about the platform. Pricing details are available with a team consultation. They do not offer any free trial.
10. TensorFlow 2.0 AI Software
TensorFlow (TF) is a Python-based open-source end-to-end numerical computation and machine learning platform. Developers use it to build large-scale multi-layered neural network-based models. Created by Google, it is one of the most popular AI 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. I.e., Viso Suite provides a simplified interface to create AI applications with TensorFlow scaling to thousands of edge devices.
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
- In browser
It is useful for various tasks in image recognition, AI video analytics, and detection, time series, voice recognition, etc.
This AI software contains a computer vision library that 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.
11. H2O.ai
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 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 14 days. From public list prices, we can see that the H2O Driverless AI subscription starts at $300,000.
12. C3 AI Software
C3 AI, or C3.ai, provides enterprise AI software-as-a-service (Saas) for building applications and promoting 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. These include 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 AI Software
The IBM Watson platform allows organizations to automate complex machine learning processes, predict future outcomes, and optimize employee productivity. IBM offers both pre-trained models and custom model training for data analysis, pattern recognition, and predictive analytics.
Update: As of December 1st, 2023, IBM discontinued its IoT Platform Service from IBM Watson. This means that third-party software products/services are a requisite for deployment, connectivity, and Edge AI.
A free demo that gives 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.
14. DataRobot
DataRobot is an automated machine learning platform that helps organizations accelerate the development of predictive models and uncover insights from data analysis. It is for data scientists, developers, and business analysts to build and deploy high-quality models quickly and efficiently.
The cost of DataRobot varies depending on the plan, with options ranging from an individual subscription to enterprise options.
In the AWS marketplace, DataRobot AI Cloud starts from USD 98,000, with a starter pack from AutoML, AutoTS, MLOps, 5 users, and standard support.
15. Tractable
Tractable is an AI-driven platform meant to empower automotive, industrial, and insurance industries by providing automated and efficient solutions for accident assessment. It assesses damaged vehicles, accelerates the claims processing workflow, and streamlines operations.
Built with a focus on accuracy, Tractable utilizes computer vision to detect and accurately estimate vehicle repair costs. Tractable trained its AI algorithms on millions of images from previous accidents. This enables it to rapidly process and analyze car damage in seconds. Thus, 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 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.
17. Synthesia
Synthesia is an emerging leader in the AI-driven avatar industry. The company provides a software platform for video content creation through advanced synthetic video technology. With generative AI, their technology transforms physical video production into an entirely digital process. This saves 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 are many AI avatars available, with over 120 AI voices and ready-to-use video templates.
Synthesia’s product starts 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.
18. Empower by Ringover
Ringover is a well-known player in the customer experience field. They’ve developed Empower as an intelligent tool to help businesses unlock customer and prospect insights with conversational AI. Empower seamlessly integrates into businesses’ existing tech stacks, including Salesforce, Pipedrive, and Hubspot, and offers four valuable features:
- Call summary and analysis
- Automatic topic detection
- Advanced analytics
- Call library
These features make it possible to track sales call effectiveness, accelerate teams’ skills development, cut down on call times, and better understand target markets. You can start out using Empower with a free trial, while plans start at $69 per month.
Trends in Business and Enterprise AI Software
AI Software Technology Trends
The convergence of key technologies drives AI progress: Cloud Computing, Big Data, AI, and the Internet of Things. Hence, it is now becoming possible to solve problems previously deemed unsolvable at massive scales.
Edge Computing is a distributed computing paradigm bringing enterprise applications closer to data sources like IoT or Edge Devices. Edge AI, or Edge Intelligence is the concept of leveraging a combination of those technologies.
This Edge AI technology makes processing big data generated by connected IoT devices at the network edge possible. By moving workloads from the cloud to the network edge, we can build efficient, connected, robust, and scalable AI systems. Check out the cost of computer vision to learn about the immense impact of software architectures, Cloud vs. Edge.
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 and integration management with hardware and software, businesses can adopt AI technology. In return, it greatly improves the productivity of the development team by a factor of 10-100x.
Cloud AI software is increasingly replacing AI software for PC and on-premise deployments. This provides tools and fully managed AI programs that are accessible directly via browser. Such solutions do not require users to install a software client, enabling a dramatically better user experience and collaboration. Hence, users do not have to download sensitive training data or even models to their local machines.
Enterprise Applications of AI Software
With a growing number of enterprise use cases, organizations implement broad AI strategies to keep up with disruptive technologies.
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
- In-store retail analytics
- Animal monitoring in agriculture, and many more.
What’s next for AI Software?
As various branches of AI continue to mature, intelligent technology will become much more widely adopted across industry lines. By integrating it into existing processes and tech stacks as early as possible, firms can gain a competitive advantage from the jump as early innovators in their domains.
Firms must consider the time and cost savings AI can provide. From data analytics to natural language processing and computer vision, AI and machine learning have the propensity to free up time-heavy manual processes for employees to focus on tasks requiring more strategic thought.
Staying Up to Date with AI Developments
Researchers and practitioners seem to make breakthroughs in AI almost daily. To stay up to date with the latest advancements, we suggest following the viso.ai blog, PapersWithCode, and Arxiv. Here, you’ll be able to find the latest scientific papers as well as commentaries from experts in the field.
Implementing Enterprise Computer Vision
Viso Suite makes it possible for enterprise teams to start leveraging the power of state-of-the-art computer vision. By consolidating the entire machine learning pipeline into a unified infrastructure, it is now possible to manage every step in the application lifecycle. This omits the need to string together point solutions and superfluous tools.
To build computer vision and evaluate enterprise AI software platforms, please book a demo with our team. We will assist with the evaluation process to find the best AI program or platform for your use case.
