Monday, July 31, 2023

ChatGPT is a language model developed by OpenAI that interacts with users conversationally. It allows you to have a human-like conversation with the AI

ChatGPT is a language model developed by OpenAI that interacts with users conversationally. It allows you to have a human-like conversation with the AI tool, which has the ability “to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”

Enterprise users can use ChatGPT to brainstorm ideas, create first drafts, generate outlines, email ideas or discuss complex concepts. While ChatGPT offers many benefits, some companies have banned or limited its usage by their employees for compliance reasons and to prevent the release of confidential information. Some of these companies include Amazon, Apple, JP Morgan, Accenture, Verizon, and more.

We recommend using this tool in line with your company’s policies.

Key features

  • Responds to natural language queries.
  • Conversational abilities.
  • Ability to generate codes and can be used to debug codes.
  • Ability to create long and short forms of content.
  • It has text, audio, and image models.

Pros

  • Helps with the user’s research process.
  • Available 24/7.
  • Fast response time.

Cons

  • Potential bias from the data used to train the model.
  • It cannot be used as an authoritative source of information.
  • Limited accuracy.

Pricing

ChatGPT pricing varies based on your chosen model and prompt.

  • GPT-4 8K context prompt cost $0.03 per 1K tokens.
  • GPT-4 32K context prompt cost $0.06 per 1K tokens
  • GPT-3.5-turbo model costs $0.002 per 1K tokens.

Its image models start from $0.016 per image for 256×256 resolution, 512×512 costs $0.018 per image, and 1024×1024 costs $0.020 per image. The audio model (Whisper) costs $0.006 per minute.

Also see: Generative AI Companies: Top 12 Leaders

Microsoft icon

Azure Machine Learning Studio: Best for Data Scientists

Azure Machine Learning Studio is a solution designed to help ML engineers and data scientist train and deploy models and manage the MLOps lifecycle. With this tool, users can create a model in Azure Machine Learning or use a model built from an open-source platform, such as PyTorch, TensorFlow, or scikit-learn.

They can also design and build custom models and algorithms to gain insights from data, deploy them in production, and monitor the models’ analytics results as they evolve. Azure Machine Learning Studio offers several features that simplify data science and machine learning. These include automated machine learning, model management, and interactive visualizations.

Key features

  • Data labeling and preparation capability.
  • Automated machine learning.
  • Drag and drop designer.
  • Open-source libraries and frameworks.
  • Hybrid and multi-cloud model training and deployment.
  • Monitoring and analysis.

Pros

  • Users find the drag-and-drop designer beneficial.
  • Highly scalable and easy to use.
  • Documentation is comprehensive and efficient technical support.

Cons

  • Learning curve for new users.
  • Some users say the tool is pricey.

Pricing

Azure Machine Learning Studio (classic) pricing is available in two tiers: Free and Standard.

The standard plan costs $9.99 per ML studio workspace per month or $1 per studio experimentation hour.

For the production Web API pricing

  • Dev/Test: $0 per month.
  • Standard S1: $100.13 per month.
  • Standard S2: $1,000.06 per month.
  • Standard S3: $9,999.98 per month.

Also see: Generative AI Examples 

DataRobot icon

DataRobot AI Platform: Best for Predictive Modeling

DataRobot AI platform is an automated, end-to-end platform for developing and deploying AI models. It helps organizations process and analyze data to derive insights. The platform provides tools and resources for data science teams to build, tune, and deploy models. It allows users to explore models from various algorithms to select the best-fit models for their datasets. DataRobot AI platform can be deployed as multi-tenant SaaS, single-tenant SaaS, self-managed VPC and self-managed on-premise.

Key features

  • Prepare modeling data.
  • Ability to build models.
  • Validate and govern models.
  • Integration with third-party services like GitHub, Hugging Face, Streamlit, Azure Machine, Amazon SageMaker, mlflow, and Apache Airflow.
  • Supported data platforms include Snowflake, Google Cloud Storage, Amazon S3, Amazon Redshift, Google Big Query, Azure Synapse Analytics, SAP, Databricks, and Micro Azure Data Lake.
  • Supported business apps and intelligence SAP, Salesforce, Power BI, Tableau and ThoughtSpot.

Pros

  • It helps users make business decisions.
  • Real-time predictions.
  • Service health monitoring.
  • Automated compliance documentation.

Cons

  • The software is expensive.
  • Users may find the platform complex to setup.
  • Users say DataRobot model retraining automation could be more flexible.

Pricing

Data Robot doesn’t advertise its solution price on its page. However, they offer two plans: Essential 9.0 and Business Critical 9.0. Publicly available pricing on AWS and Azure marketplace shows that DataRobot AI Cloud Platform Starter Pack (for up to 5 users; standard support), which includes AutoML, Automated Time Series and MLOps, costs $98,000 per year.

On a related topic: The Future of Artificial Intelligence

Google AI Platform: Best for Research and Training Models

Google AI platform provides many different AI capabilities that enable developers and businesses to build and deploy AI-powered applications and solutions. It offers generative AI solutions based on PaLM LLM, Google Bard, which is a conversational AI chat service that functions like ChatGPT – it can generate text based on queries and is also able to generate code.

Google also offers data science solutions like Vertex AI, AutoML, Spark on Google Cloud and BigQuery ML, as well as responsible AI services.

Key features

  • Low-latency serving.
  • Data discovery and ingestion.
  • Supports TPUs.
  • Text-to-speech and speech-to-text capability.
  • Contact Center AI service to improve operational efficiency.

Pros

  • Large scale training.
  • Google TensorFlow product can be used to scale resources across CPUs, GPUs, and Cloud TPUs.
  • Easy to train models.

Cons

  • Steep learning curve for new users.
  • Some users say training and documentation can be improved.

Pricing

Google AI services pricing vary based on your selected solution. Contact Google’s sales team for custom quotes.

On a related topic: What is Generative AI?

Tidio icon

Tidio: Best for Customer Success Teams

Tidio is a live chat and chatbot platform for customer support, sales, and marketing. It allows businesses to communicate with customers and visitors in real time and analyze and optimize their conversations. It offers a suite of features, including automated chatbot responses, integrated messaging apps, AI-based automated responses, and integrations with third-party software.

Key features

  • Messenger, Instagram, email integration.
  • Live chat conversations.
  • Chatbot triggers.
  • Analytics capability.
  • Native Shopify actions.
  • Live chat conversations.
  • Offer various chatbots, including sales chatbot templates, FAQ chatbot templates, visual chatbot builders and AI chatbots.

Pros

  • Easy to setup and use.
  • Allow for real-time communication with customers.
  • Mobile apps option.

Cons

  • Some users say the tool is pricey.
  • AI Chatbots is only available for the Tidio+ plan.

Pricing

Tidio offers various pricing plans, one free and five paid plans.

  • Free: No cost for up to three seats, 50 live chat conversations, 100 chatbot triggers and unlimited tickets.
  • Starter: $29 per month for up to three seats, 100 live chat conversations, 500 chatbot triggers and unlimited tickets.
  • Communicator: $19 per month per seat – for up to three seats, unlimited live chat conversations, 100 chatbot triggers and unlimited tickets.
  • Chatbots: Starts from $19 per month for up to three seats, 50 live chat conversations, 1K to 40K chatbot triggers and unlimited tickets.
  • Chatbots and communicator (bundle plan): Starts from $19 per month plus $19 per month per seat.
  • Tidio+: It’s a personalized plan designed for various enterprise use cases. It starts from $329 per month.

Also see: Top Generative AI Apps and Tools

Murf AI icon

Murf AI: Best for Text to Speech

Murf.ai is a text-to-speech artificial intelligence platform that provides high-quality natural-sounding AI voices. It enables users to create voice-over content,  podcasts, and more. Murf.ai offers many features, including text-to-speech generation, powerful voice-editing capabilities, and an intuitive web-based interface.

It also provides a range of features and customization options to help users get the most out of their experience. Users can filter their desired voice to a particular age demographic, including young, middle-aged, as well as gender.

Murf AI supports over 20 languages, including English, Russian, Korean, Romanian, Tamil, Finnish, Dutch, Arabic, and Chinese.

Key features

  • Has over 20 languages and accents.
  • Users can add video, music, or image.
  • It allows users to set their desired speed, pitch, emphasis and interjections.
  • Customization capability.
  • Voices for various purposes, including marketing, author, managers and more.

Pros

  • Deletion recovery for enterprise plan.
  • High-quality voices.
  • Extensive voice options.
  • Intuitive and easy to navigate and use user interface.

Cons

  • Users say they experience inaccurate pronunciation.
  • Users say Murf AI is expensive.

Pricing

Murf AI offers a free plan for up to three users and three paid plans for up to 25 users.

  • Free: No cost for up to three users. It includes 10 minutes of voice generation and 10 minutes of transcription with access to all 120+ voices. But it lacks download capability.
  • Basic: $29 per user per month, billed monthly or $19 per user per month, billed annually – for up to 10 users. It includes access to 60 basic voices, 10 languages and two hours of voice generation per user per month. Unlimited download is available for this plan.
  • Pro: $39 per user per month, billed monthly or $26 per user per month, billed annually – for up to 10 users. It includes access to all 120+ voices, over 20 languages and accents and four hours of voice generation per user per month, plus two hours of transcription per user per month. Unlimited download is available for this plan.
  • Enterprise: $99 per user per month, billed annually only. It includes unlimited voice generation, transcription and storage.

On a related topic: The AI Market: An Overview

H2O.ai icon

H20.ai: Best for Building Custom Generative AI Models

H2O.ai is a leading AI Cloud company with over 10 years of experience providing AI and ML solutions. The company’s goal is to democratize AI and make it accessible to organizations of all sizes. H2O.ai also offers an open source generative AI platform, h2oGPT, which provides tools (H2O LLM Studio, a framework and no-code GUI) for data scientists and developers to build and deploy large language models.

H2O.ai offers several products and services built on top of the H2O platform. Some of their notable offerings include: H2O AI Cloud, which provides comprehensive automated machine learning (autoML) capabilities, H2O-3, built on various algorithms, H2O Driverless AI, which automates some complex data science and machine learning workflows such as feature engineering, model validation, model tuning, model selection, and model deployment, H2O document AI and more.

Key features

  • Distributed, in-memory processing.
  • AutoML capability.
  • Uses various algorithms, including Random Forest, GLM, GBM, XGBoost, GLRM, Word2Vec, for distributed computing and for both supervised and unsupervised techniques.

Pros

  • Quality customer support.
  • Open source products.
  • Promote AI collaboration.

Cons

  • Documentation can be improved.

Pricing

H2O.ai doesn’t advertise its rates on its website. They encourage interested buyers to request a demo, and quotes will be sent after the demo based on the buyer’s needs. Publicly available pricing shows that H2O AI Cloud costs $50,000 per unit with a minimum of 4 AI units.

Also see: ChatGPT vs GitHub Copilot 

Fireflies.ai icon

Fireflies AI: Best Notetaking AI Assistant for Meetings

Fireflies.ai is an AI-powered meeting note-taking platform that automates the process of capturing meeting information, including audio transcripts, text notes, and highlights. It uses machine learning and natural language processing (NLP) to transcribe meeting recordings and provide users with actionable notes to save them hours of manual post-meeting note-taking and follow-up.

Key features

  • Chrome extension.
  • CRM, Zapier, and Slack integrations.
  • Playback speeds: 1x, 1.25x, 1.5x, 1.75x, 2x.
  • Users can create meeting clips as soundbites.
  • Record Zoom, Google Meet, and MS Teams.

Pros

  • Time stamped notes.
  • Speaker talk-time analytics.
  • Easy to setup and use.

Cons

  • Occasionally slow.
  • The search capability can be made better.

Pricing

  • Free: No cost for up to 800 mins of storage.
  • Pro: $10 per seat per month, billed annually or $18 per seat per month, billed monthly.
  • Business: $19 per seat per month, billed annually or $29 per seat per month, billed monthly.
  • Enterprise: Contact the Fireflies sales team for a custom quote.

Also see: Generative AI Startups 

Amazon Web Services icon

AWS AI Services: Best for Features

AWS (Amazon Web Services) offers a range of AI services that allow developers to incorporate advanced machine learning capabilities into their applications. Here are the prominent AI services provided by AWS:

AWS computer vision

  • Amazon Rekognition: For analyzing images and videos.
  • Amazon Lookout for Vision: For detecting defects and automate inspection.
  • AWS Panorama: Helps Utilize computer vision at the edge.

Automated data extraction and analysis

  • Amazon Textract: Extract text and data.
  • Amazon Comprehend: For gathering insights.
  • Amazon A2I: For quality control.

Language AI

  • Amazon Lex: For building conversational interfaces like chatbots and virtual agents.
  • Amazon Transcribe: Transcribe is an automatic speech recognition service that can convert speech into written text.
  • Amazon Polly: This service converts text into lifelike speech using advanced deep-learning technologies.

Amazon also offers other AI services like Amazon Kendra, Personalized and Translate to improve customer experience, as well as business metrics services such as Amazon Forecast, Amazon Fraud Detector, and Amazon Lookout for Metrics. DevOps teams can leverage AWS AI service code tools like Amazon DevOps Guru, Amazon CodeGuru Reviewer and Amazon CodeGuru Profiler.

Those looking for industrial AI tools may find Amazon Lookout for Equipment and Amazon Montron beneficial. Healthcare workers can use Amazon Healthlake to store and analyze health data and Amazon Comprehend Medical to extract health data.

Key features

  • Integration with Other AWS Services.
  • Developer-Friendly APIs.
  • Offer pre-trained models.
  • Deep learning capabilities.

Pros

  • Scalability and flexibility.
  • Easy integrations.
  • Impressive and broad AI and ML services.
  • Excellent training material and documentation.

Cons

  • Customer support can be improved.
  • Billing can be confusing.

Pricing

AWS AI service pricing depends on your desired solution. To get an idea about how much you may pay for a particular service, you can use the AWS pricing calculator to get an estimate.

Also see: Generative AI Startups

Jupyter icon

Jupyter Notebooks: Best for Creating and Sharing Computational Documents

Jupyter Notebooks is an open-source web application that allows you to create and share documents containing code and data. It provides an interactive computing environment where you can combine code execution, data visualization, and textual explanations in a single document.

Jupyter Notebooks are commonly used in data analysis, machine learning, scientific computing, and education.

Key features

  • Supports over 40 programming languages, including Scala, Python, Julia, and R.
  • Integrates with big data tools like Apache Spark and R.
  • Data preparation, exploration and platform data modeling.

Pros

  • Easy to use.
  • Data visualization capability.
  • Users can use this tool to practice Python for data science.

Cons

  • The user interface can be improved.
  • Users say the tool lags sometimes.

Pricing

Free to install and use.

For more information: AI vs. ML

Chorus icon

Chorus.ai: Best for Client-Facing and Sales Team

Chorus is a conversation intelligence and calls recording solution that helps users analyze all customer engagements across video conferencing, phone calls, and email channels to learn about their performance in the meeting to convert prospects into pay customers.

It provides action items, advanced analytics, custom scoring, conversation tags, and advanced AI-driven insights to help teams modify actions for better customer conversations.

Key features

  • Sales call analysis.
  • Deal intelligence and pipeline management.
  • Snippet tool.
  • Automatically join Zoom meetings.
  • Talk time percentages.
  • Supported languages include German, English, French, Italian, Japanese, Dutch, Portuguese, Spanish, and Chinese (Traditional).

Pros

  • Users praise Chorus.ai’s transcript and recorder capabilities.
  • Review each speaker’s speech.
  • Quality meeting recording.

Cons

  • Transcriptions for non-native English speakers can be improved.
  • Search functionality can be improved.

Pricing

ZoomInfo, which acquired Chorus.ai, doesn’t publicly advertise its pricing on its website. However, the company pricing page shows that they offer three plans: SalesOS, MarketingOS, and TalentOS. ZoomInfo usually charges based on your required features, functionality, license number, and credit usage.

Publicly available data shows each plan’s base pricing.

  • SalesOS: Base platform access, bulk credits and premium features cost $34,995 for 12 months, $69,990 for 24 months, and $104,985 for 36 months.
  • MarketingOS: ABM Pro+ access and additional premium add-ons cost $69,995 for 12 months, $139,990 for 24 months, and $209,985 for 36 months.
  • OperationsOS: Enrich Premium+, 0-250k records costs $39,000 for 12 months, $78,000 for 24 months, and $117,000 for 36 months.
  • TalentOS: Base Platform Access (includes Americas, APAC, and non-GDPR EU Data) costs $15,000 for 12 months, $30,000 for 24 months, and $45,000 for 36 months.

Also see: Cloud and AI Combined: Revolutionizing Tech

AI Software Benefits

AI software offers several benefits to businesses, including:

  • Enhanced decision-making: With its ability to evaluate large datasets, enterprise users can gain helpful insights from their AI software. It can identify patterns, trends, and correlations that may not be readily apparent to human analysts, enabling businesses to make data-driven decisions and stay ahead of the competition.
  • Cost reduction: Automating tasks and optimizing processes minimizes or eliminates costly errors and the need for manual intervention in various areas, resulting in cost savings for businesses.
  • Personalized customer experiences: By analyzing customer data and behavior patterns, you can provide services tailored to your customer’s needs and offer customized customer support. It will boost your retention, loyalty and customer satisfaction rates.
  • Workforce augmentation: AI software can augment human capabilities and expertise, leading to a more skilled and efficient workforce. It can assist employees in their tasks, provide real-time guidance and recommendations, and enable them to leverage AI-generated insights effectively. This collaborative approach between humans and AI improves overall business operational performance and ultimately leads to increased revenue.
  • Competitive advantage: Companies can gain a competitive edge in the market by leveraging AI tools, from optimizing marketing campaigns to improving sales forecasting and enabling better product development. It allows enterprises to drive innovation and capture the market early with innovations and solid solutions.

How to Choose the Best AI Software

Choosing the best AI software for your company can be challenging, as there are various factors to consider. Here are some steps to help you make an informed decision:

  • Identify your business needs; how exactly will you use this software?
  • Clearly outline the goals you want to achieve with AI software.
  • Assess technical requirements – consider scalability, compatibility with existing infrastructure, programming language support, and data integration capabilities.
  • Assess the learning curve for your team and consider the availability of training resources, documentation, and support from the software provider.
  • Evaluate customization options to determine whether the AI software can be tailored to your business needs.
  • Analyze the algorithmic capabilities – consider whether the software supports deep learning, machine learning, natural language processing, or other AI techniques relevant to your needs.
  • Check for data privacy and security.
  • Read user reviews and case studies.
  • Consider vendor reputation and support.
  • Conduct trials and demos.
  • Consider the total cost of ownership (TCO).
  • Seek expert advice if needed – If you lack in-house expertise, consider consulting with AI experts or engaging a trusted technology advisor who can guide you based on your business needs and industry requirements.

These steps help streamline selecting the best AI tool for your business – endeavor to choose software that aligns with your specific needs, technical capabilities, and long-term goals.

Bottom Line: the Best AI Software

There are thousands of AI software applications and services available, and many more that are being released to the market daily, all built with a simple goal – to automate and simplify complex processes – to help businesses derive better outcomes.

Regardless of your industry, team sizes, functions and technical expertise, there is an AI software solution that can help optimize your current business process. You should use these tools responsibly to protect your enterprise data.

Building artificial intelligence (AI) tools for your business


Building artificial intelligence (AI) tools for your business is becoming more mainstream with the advancement of AI development software. AI and machine learning (ML) projects require a lot of advanced systems working altogether. So it makes sense for developers to use a platform that does most of the heavy lifting.


The best AI development software can provide the framework and tools to develop tailor-made AI tools for a variety of applications. This article explores some of the top platforms used today.

What is AI Development Software?

AI development software is software that allows users and businesses to build powerful AI tools to streamline various tasks with amazing speed and efficiency. You’re probably familiar with some popular AI tools already developed. 

Although these AI tools are great out-of-the-box solutions for many, developers are finding it easier than ever before to use AI development software to build custom AI tools to meet more specific needs. Developers can even use drag-and-drop interfaces and other helpful no-code features, depending on the platform.

With AI development software, online stores are building custom chatbots for more conversions and better customer service. Businesses are using custom AI machine learning software to generate advanced data reports to grow revenue. And that is just the tip of the iceberg.
Types of AI Development Software

In general, the best software for developing AI tools will usually offer the following types of solutions: AI Development Platforms: These comprehensive solutions enable the construction of AI applications from the ground up. Featuring an extensive selection of pre-built algorithms and an accessible interface, they simplify designing and adapting AI models with user-friendly elements such as drag-and-drop capabilities. These platforms accommodate developers with varying skill levels and serve as a versatile base for AI projects.
Deep Learning: Focus on training artificial neural networks inspired by the human brain for tasks requiring human-like intelligence. Utilizing architectures like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), deep learning software is applied across various fields, including computer vision, natural language processing, and speech recognition. These tools often rely on large datasets, powerful computational resources, and advanced optimization techniques to improve model performance.
Machine Learning: Enable computers to learn from data by identifying patterns and relationships. These tools use various algorithms and techniques, such as decision trees, clustering, and regression analysis, to build predictive models that can make data-driven decisions and adapt over time as new data becomes available.
Conversational AI: Focuses on simulating human-like conversations, enabling developers to create interactive and responsive conversational agents. These tools use natural language processing and other AI techniques to effectively understand and respond to user inputs.

The best AI dev platforms will have pre-trained models, easy-to-use user interfaces (UI), and plenty of support material to get one’s bearings.
What are the Best AI Development Software and Platforms?

If you’ve been looking into AI development, you’ve likely heard many of these big names. But we’ll give an overview of the top development platforms to give you a good idea of their capabilities.


The Best AI Development Software Listed In Order

Google Cloud AI Platform
Microsoft Azure AI
IBM Watson
Infosys XtractEdge
H2O.AI
Google Dialogflow
BigML
Viso Suite
Observe.AI




Google Cloud AI Platform is a cloud-based service that allows developers to build, train, and deploy machine learning models with popular frameworks. With plenty of widely adopted pre-trained models, AI developers can quickly start building their own tools with the basics covered.
Key Features: Support for popular frameworks, including TensorFlow and Scikit-learn
Built-in algorithms for tasks such as image and speech recognition, NLP, and predictive analytics
A scalable and easy-to-use platform for building, training, and deploying ML models
Plenty of documentation to help learn the platform and create advanced products


Shopify is making use of Google’s Discovery AI to give advanced online retailers access to advanced product search based on AI – 

See Shopify Commerce Components

VISIT GOOGLE CLOUD AI PLATFORM

2. Microsoft Azure AI

Building artificial intelligence (AI) tools for your business is becoming more mainstream with the advancement of AI development software. AI and machine learning (ML) projects require a lot of advanced systems working altogether. So it makes sense for developers to use a platform that does most of the heavy lifting.  The best AI development software can provide the framework and tools to develop tailor-made AI tools for a variety of applications. This article explores some of the top platforms used today.  What is AI Development Software?  AI development software is software that allows users and businesses to build powerful AI tools to streamline various tasks with amazing speed and efficiency. You’re probably familiar with some popular AI tools already developed.   Although these AI tools are great out-of-the-box solutions for many, developers are finding it easier than ever before to use AI development software to build custom AI tools to meet more specific needs. Developers can even use drag-and-drop interfaces and other helpful no-code features, depending on the platform.  With AI development software, online stores are building custom chatbots for more conversions and better customer service. Businesses are using custom AI machine learning software to generate advanced data reports to grow revenue. And that is just the tip of the iceberg. Types of AI Development Software  In general, the best software for developing AI tools will usually offer the following types of solutions: AI Development Platforms: These comprehensive solutions enable the construction of AI applications from the ground up. Featuring an extensive selection of pre-built algorithms and an accessible interface, they simplify designing and adapting AI models with user-friendly elements such as drag-and-drop capabilities. These platforms accommodate developers with varying skill levels and serve as a versatile base for AI projects. Deep Learning: Focus on training artificial neural networks inspired by the human brain for tasks requiring human-like intelligence. Utilizing architectures like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), deep learning software is applied across various fields, including computer vision, natural language processing, and speech recognition. These tools often rely on large datasets, powerful computational resources, and advanced optimization techniques to improve model performance. Machine Learning: Enable computers to learn from data by identifying patterns and relationships. These tools use various algorithms and techniques, such as decision trees, clustering, and regression analysis, to build predictive models that can make data-driven decisions and adapt over time as new data becomes available. Conversational AI: Focuses on simulating human-like conversations, enabling developers to create interactive and responsive conversational agents. These tools use natural language processing and other AI techniques to effectively understand and respond to user inputs.  The best AI dev platforms will have pre-trained models, easy-to-use user interfaces (UI), and plenty of support material to get one’s bearings. What are the Best AI Development Software and Platforms?  If you’ve been looking into AI development, you’ve likely heard many of these big names. But we’ll give an overview of the top development platforms to give you a good idea of their capabilities.  The Best AI Development Software Listed In Order Google Cloud AI Platform Microsoft Azure AI IBM Watson Infosys XtractEdge H2O.AI Google Dialogflow BigML Viso Suite Observe.AI  1. Google Cloud AI Platform   Google Cloud AI Platform is a cloud-based service that allows developers to build, train, and deploy machine learning models with popular frameworks. With plenty of widely adopted pre-trained models, AI developers can quickly start building their own tools with the basics covered. Key Features: Support for popular frameworks, including TensorFlow and Scikit-learn Built-in algorithms for tasks such as image and speech recognition, NLP, and predictive analytics A scalable and easy-to-use platform for building, training, and deploying ML models Plenty of documentation to help learn the platform and create advanced products   Shopify is making use of Google’s Discovery AI to give advanced online retailers access to advanced product search based on AI –   See Shopify Commerce Components  VISIT GOOGLE CLOUD AI PLATFORM  2. Microsoft Azure AI     Microsoft Azure AI offers enterprise-ready AI services and tools for building, deploying, and managing AI solutions at scale, including machine learning, deep learning, and cognitive benefits. It also is a go-to platform for pre-trained models that developers can leverage immediately and trust that the foundation is reliable.  Key Features: Offers tools for machine learning, deep learning, and cognitive services Integrates with popular development tools like Visual Studio and GitHub Scalable platform for building, deploying, and managing AI solutions at scale Allows AI developers to create custom AI models   VISIT MICROSOFT AZURE AI  3. IBM Watson     IBM Watson is a conversational AI platform built for question-and-answer use cases. It utilizes NLP, ML, and knowledge representation to find the meaning of a question and then generate accurate responses. It’s used in many business use cases; primarily customer support applications.  Key Features: Leverages machine learning, deep learning, and natural language processing techniques Pre-built AI services, APIs, and development tools System integration for customer services, healthcare, and education applications   VISIT IBM WATSON  4. Infosys XtractEdge     Infosys XtractEdge is an AI platform developed by Infosys that helps businesses automate complex business processes, improve productivity, and gain valuable insights using machine learning, deep learning, and natural language processing. It primarily does all this through information extraction from documents.  Key Features: Leverages ML and NPL to mine information hidden within documents Converts non-text information (images) to text using optical character recognition (OCR) so it can be processed Can automate document data extraction   VISIT INFOSYS NIA  5. H2O.AI        H2O.AI offers an open-source machine learning platform that enables developers to build and deploy AI models at scale. It features pre-trained, open-source AI models and algorithms. Its open-source nature allows developers to self-host their models or choose options for either on-premises or cloud deployments.  Key Features: Offers an open-source AI platform Primarily built for business applications Flexible deployment solutions for choosing the exact security control needed   VISIT H2O.AI  6. Google Dialogflow     Google Dialogflow is a chatbot-building service (under Google Cloud AI) that allows developers to construct conversational agents using NLP and integrate them with external messaging platforms. Developers submit standard questions and answers to those questions to the platform. From there, individual phrases and words can be categorized to train it on how they are commonly used and understood. DialogFlow then uses that categorization to learn how to respond to similar questions based on that training.  Many top AI Chatbots and customer support platforms integrate directly with DialogFlow to help create advanced bots for customer support and other purposes. Among the best are LandBot, Ubisend, and Trengo.  Key Features: Enables developers to build conversational interfaces using natural language processing  Allows developers to integrate chatbots with various messaging platforms and voice assistants An easy-to-use interface that is less technical than other NLP solutions   VISIT GOOGLE DIALOGFLOW  7. BigML     BigML is a cloud-based machine-learning platform that offers tools and algorithms to help developers build and deploy predictive models using machine-learning techniques such as decision trees, random forests, and deep neural networks. It’s one of the easiest platforms to start using.  Key Features: The platform that lets you build, deploy, and manage custom AI models Applies machine learning algorithms, like decision trees, random forests, and deep neural networks Has on-premises and cloud deployment options  VISIT BIGML  8. Viso Suite     Viso Suite is an AI-powered computer vision software platform. It provides a comprehensive computer vision application development platform that is meant to be used by businesses to create their own applications. This can help monitor traffic, count inventory, and so much more.  Key Features: Combines powerful computer vision with an application development platform The low-code solution that can speed up the development of advanced AI systems Pre-built integrations to make the low-code environment even more agile   VISIT VISO SUITE  9. Observe.AI   Observe.AI is an AI-powered call center solution that uses natural language processing and speech recognition to analyze and transcribe customer conversations in real-time. The benefits are that it enables businesses to gain insights into customer sentiment, identify trends, and improve agent performance at scale. AI developers working on customer experience (CX) and support can use Observe to increase the speed of insight adoption drastically.  Key Features: Speech recognition, transcription, and NLP layered into a powerful voice platform Analytics capabilities to see what’s going on across an entire support organization Deep analytics and insights to fix problems and capitalize on top performance trends   VISIT OBSERVE.AI  What is the Best AI Development Software?  Google Cloud AI Platform and Microsoft Azure AI stand out as the top AI development software options available today.  Google Cloud AI Platform best suits developers seeking a scalable, cloud-based service that supports popular frameworks like TensorFlow and Scikit-learn. It offers powerful built-in algorithms, perfect for handling tasks such as image recognition and natural language processing.  On the other hand, Microsoft Azure AI is an excellent choice for organizations looking to build, deploy, and manage AI solutions at scale using an enterprise-ready suite of AI services and tools. It seamlessly integrates with popular development tools like Visual Studio and GitHub, providing a robust and efficient environment for businesses to harness the power of AI.


Microsoft Azure AI offers enterprise-ready AI services and tools for building, deploying, and managing AI solutions at scale, including machine learning, deep learning, and cognitive benefits. It also is a go-to platform for pre-trained models that developers can leverage immediately and trust that the foundation is reliable.

Key Features: Offers tools for machine learning, deep learning, and cognitive services
Integrates with popular development tools like Visual Studio and GitHub
Scalable platform for building, deploying, and managing AI solutions at scale
Allows AI developers to create custom AI models


VISIT MICROSOFT AZURE AI

3. IBM Watson



IBM Watson is a conversational AI platform built for question-and-answer use cases. It utilizes NLP, ML, and knowledge representation to find the meaning of a question and then generate accurate responses. It’s used in many business use cases; primarily customer support applications.

Key Features: Leverages machine learning, deep learning, and natural language processing techniques
Pre-built AI services, APIs, and development tools
System integration for customer services, healthcare, and education applications


VISIT IBM WATSON

4. Infosys XtractEdge



Infosys XtractEdge is an AI platform developed by Infosys that helps businesses automate complex business processes, improve productivity, and gain valuable insights using machine learning, deep learning, and natural language processing. It primarily does all this through information extraction from documents.

Key Features: Leverages ML and NPL to mine information hidden within documents
Converts non-text information (images) to text using optical character recognition (OCR) so it can be processed
Can automate document data extraction


VISIT INFOSYS NIA

5. H2O.AI






H2O.AI offers an open-source machine learning platform that enables developers to build and deploy AI models at scale. It features pre-trained, open-source AI models and algorithms. Its open-source nature allows developers to self-host their models or choose options for either on-premises or cloud deployments.

Key Features: Offers an open-source AI platform
Primarily built for business applications
Flexible deployment solutions for choosing the exact security control needed


VISIT H2O.AI

6. Google Dialogflow



Google Dialogflow is a chatbot-building service (under Google Cloud AI) that allows developers to construct conversational agents using NLP and integrate them with external messaging platforms. Developers submit standard questions and answers to those questions to the platform. From there, individual phrases and words can be categorized to train it on how they are commonly used and understood. DialogFlow then uses that categorization to learn how to respond to similar questions based on that training.

Many top AI Chatbots and customer support platforms integrate directly with DialogFlow to help create advanced bots for customer support and other purposes. Among the best are LandBot, Ubisend, and Trengo.

Key Features: Enables developers to build conversational interfaces using natural language processing

Allows developers to integrate chatbots with various messaging platforms and voice assistants
An easy-to-use interface that is less technical than other NLP solutions


VISIT GOOGLE DIALOGFLOW

7. BigML



BigML is a cloud-based machine-learning platform that offers tools and algorithms to help developers build and deploy predictive models using machine-learning techniques such as decision trees, random forests, and deep neural networks. It’s one of the easiest platforms to start using.

Key Features: The platform that lets you build, deploy, and manage custom AI models
Applies machine learning algorithms, like decision trees, random forests, and deep neural networks
Has on-premises and cloud deployment options

VISIT BIGML

8. Viso Suite



Viso Suite is an AI-powered computer vision software platform. It provides a comprehensive computer vision application development platform that is meant to be used by businesses to create their own applications. This can help monitor traffic, count inventory, and so much more.

Key Features: Combines powerful computer vision with an application development platform
The low-code solution that can speed up the development of advanced AI systems
Pre-built integrations to make the low-code environment even more agile


VISIT VISO SUITE

9. Observe.AI


Observe.AI is an AI-powered call center solution that uses natural language processing and speech recognition to analyze and transcribe customer conversations in real-time. The benefits are that it enables businesses to gain insights into customer sentiment, identify trends, and improve agent performance at scale. AI developers working on customer experience (CX) and support can use Observe to increase the speed of insight adoption drastically.

Key Features: Speech recognition, transcription, and NLP layered into a powerful voice platform
Analytics capabilities to see what’s going on across an entire support organization
Deep analytics and insights to fix problems and capitalize on top performance trends


VISIT OBSERVE.AI

What is the Best AI Development Software?

Google Cloud AI Platform and Microsoft Azure AI stand out as the top AI development software options available today.

Google Cloud AI Platform best suits developers seeking a scalable, cloud-based service that supports popular frameworks like TensorFlow and Scikit-learn. It offers powerful built-in algorithms, perfect for handling tasks such as image recognition and natural language processing.

On the other hand, Microsoft Azure AI is an excellent choice for organizations looking to build, deploy, and manage AI solutions at scale using an enterprise-ready suite of AI services and tools. It seamlessly integrates with popular development tools like Visual Studio and GitHub, providing a robust and efficient environment for businesses to harness the power of AI.