20 Top Generative AI Companies Leading In 2024

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Generative AI companies are popping up everywhere and quickly. They range from established companies adding generative AI to their software products to new generative AI startups.

As generative AI rapidly develops, it can be difficult to distinguish between the leading generative AI companies and the hundreds of others that are beginning to tap into this AI technology and explore its vast potential.

To assist, this guide covers the top 20 generative AI companies, detailing their products and potential use cases. We’ll also provide analysis into how and why these generative AI companies are growing in popularity so quickly.


Top Generative AI Companies Compared

Each of these generative AI companies offers unique product portfolios and solutions that set them apart from their competition; therefore, instead of comparing them across the same core criteria, we’ll instead take a look at their key business stats, products, and market value.

In this table, we’ve covered the 10 best generative AI companies, while the rest of this guide will look at these organizations plus 10 additional generative AI leaders.

Headquarters Founded Company Size Key Products Market Cap (as of March 2024)
OpenAI San Francisco, CA, USA 2015 200-500 employees GPT-4, ChatGPT, DALL-E 3, Sora Private company valued at $80 billion+
Microsoft Redmond, WA, USA 1975 220,000+ employees Microsoft Copilot, Copilot for Microsoft 365, Microsoft Copilot Studio, Microsoft Copilot in Bing $3.01 trillion
Alphabet (Google) Mountain View, CA, USA 1998 180,000+ employees Gemini, Vertex AI, Gemini for Google Workspace $1.72 trillion
Amazon (AWS) Seattle, WA, USA 1994 1.5 million+ employees Amazon Bedrock, Amazon Q, Amazon CodeWhisperer, Amazon SageMaker $1.79 trillion
NVIDIA Santa Clara, CA, USA 1993 29,000+ employees NVIDIA AI, NVIDIA NeMo, NVIDIA BioNeMo, NVIDIA Picasso, various chips and GPUs $2.14 trillion
Anthropic San Francisco, CA, USA 2021 50-300 employees Claude 3, Claude API Private company valued at $15 billion
Cohere Toronto, ON, Canada 2019 50-300 employees Command, Embed, Chat, Generate, Semantic Search Private company valued at $2.2 billion
Glean Palo Alto, CA, USA 2019 200-500 employees Glean, Glean Chat, Glean Assistant Private company valued at $2.2 billion
Jasper Austin, TX, USA 2020 50-200 employees Jasper, Jasper API, Jasper AI Copilot Private company valued at $1.2 billion
Hugging Face Brooklyn, NY, USA 2016 100-300 employees BLOOM, AutoTrain, Inference Endpoints Private company valued at $4.5 billion

OpenAI icon.

OpenAI

Best overall

  • Headquarters: San Francisco, CA, USA
  • Founded: 2015
  • Company Size: 200-500 employees
  • Key Products: GPT-4, ChatGPT, DALL-E 3, Sora
  • Market Cap: Private company valued at $80 billion+

Since OpenAI first publicly released ChatGPT in late 2022, it has completely shaped the generative AI landscape with its innovations across different types of content generation and AI research. OpenAI is the most successful dedicated generative AI company to date, worth an estimated $80 billion+ and backed by major tech companies like Microsoft.

Beyond its flagship content generation solution, ChatGPT, and image generation solution, DALL-E, OpenAI also offers its API and different generative AI models to support companies in their own AI development efforts. GPT-4, chat models, instruct models, fine-tuning models, audio models, image models, and embedding models can all be customized for a usage fee to meet individual business needs.

Most recently, OpenAI has also announced Sora, a generative AI video solution, and the GPT Store, which will make it easier for users to select custom-built versions of ChatGPT that align with their specific business use cases and requirements.

Pros and cons

Pros Cons
Well-funded and innovative company. No real-time information informing results in free tool.
General availability of APIs and fine-tuning models. Usage-based model access can become expensive.

Pricing

OpenAI offers a wide range of products with different subscription and usage-based pricing options. We’ve covered a few of its top products below, but more pricing information can be found here.

  • ChatGPT: $0 for Free, $20 per user per month for Plus, $25-$30 per user per month for Team, and custom pricing for Enterprise plan.
  • DALL-E 3 model: Between $0.40 and $0.10 per image, depending on selected quality and resolution.
  • GPT-4 model: Between $30 and $60 per 1 million input tokens and between $60 and $120 per 1 million output tokens.

Features

  • ChatGPT chatbot with multimodal outputs based on GPT-3.5 or GPT-4, depending on selected plan.
  • DALL-E family of tools for high-quality image generation.
  • APIs, base, embedding, and fine-tuning models.
  • Sora for text-to-video content generation.
  • GPT Store for ChatGPT customizations.

To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024.

Microsoft icon.

Microsoft

Best enterprise generative AI partner and tools

  • Headquarters: Redmond, WA, USA
  • Founded: 1975
  • Company Size: 220,000+ employees
  • Key Products: Microsoft Copilot, Copilot for Microsoft 365, Microsoft Copilot Studio, Microsoft Copilot in Bing
  • Market Cap: $3.01 trillion

Microsoft is one of the most dynamic leaders in generative AI today, developing many of its own generative AI tools while supporting and funding new technologies from OpenAI. Bing, the Microsoft-owned search engine, was the first major search engine to incorporate generative AI functions via chatbot, and Microsoft’s family of Copilot technologies is one of the most far-reaching generative AI assistants on the market today.

Copilot is deeply integrated in many of Microsoft’s most popular business and enterprise tools, which are already some of the most popular business applications in use today. These are the main instances of Copilot that are available for enterprise and workplace assistance tasks:

  • Microsoft Copilot: The casual chat interface that supports text and voice inputs, document attachments, and multimodal outputs through various GPTs.
  • Copilot for Microsoft 365: Assistive content generation in Microsoft 365 apps, like Word and Excel, but also in more complex business tools, like Dynamics 365 and Power BI.
  • Copilot for Sales: This sales-focused solution works in both Dynamics 365 and Salesforce.
  • Copilot Studio: With this solution, users can customize existing Microsoft Copilot tools or build their own custom solutions.
  • GitHub Copilot: GitHub, which is owned by Microsoft, has its own copilot solution that assists with coding and other developer tasks.

Pros and cons

Pros Cons
Smooth generative AI integration with Microsoft products. Expensive solutions, especially for larger teams.
Partnership with OpenAI. Limited usability outside of Microsoft-owned products.

Pricing

Like OpenAI, Microsoft offers multiple generative AI solutions that are all priced differently; in some cases, you purchase the generative AI tool directly, while in others, it is available as part of an existing Microsoft tool subscription. We’ll cover pricing information for some of the most popular solutions in the Microsoft tool stack below:

  • Microsoft Copilot: Free for baseline version; $20 per month for Microsoft Copilot Pro.
  • Copilot for Microsoft 365: $30 per user per month, plus a Business Standard or Business Premium Microsoft 365 license.
  • Microsoft Copilot Studio: $200 for up to 25,000 messages per month.
  • GitHub Copilot: Free version; paid plans range from $10 to $39 per user per month.
  • Microsoft Copilot for Sales: $50 per user per month.

Features

  • Close partnership and collaboration with OpenAI.
  • Copilot access in Microsoft 365 apps, including Dynamics 365.
  • Custom copilot building opportunities in Copilot Studio.
  • Copilot solution in preview for Power BI.
  • AI-powered browser solutions.

For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide: 150+ Top AI Companies 2024.

Google icon.

Alphabet (Google)

Best for online, integrated generative AI solutions

  • Headquarters: Mountain View, CA, USA
  • Founded: 1998
  • Company Size: 180,000+ employees
  • Key Products: Gemini, Vertex AI, Gemini for Google Workspace
  • Market Cap: $1.72 trillion

Google has generated extra buzz around its generative AI capabilities over the past few months with its release of Gemini, a collection of generative AI models that combines the strengths of Google’s previous models, LaMDA and PaLM 2, for a scalable and multimodal content experience.

Whether users select the free or paid version of Gemini’s AI chatbot interface, they can submit multimodal inputs, receive multimodal outputs — often with relevant webpages and images included — and benefit from several different quality management and fact-checking features. Additionally, Gemini gives users the ability to turn on relevant Google extensions, ensuring that generated results not only benefit from Google Search information but also from Google Flights, Hotels, Maps, Workspace, and YouTube.

Even with these most recent innovations, the company continues to develop artificial intelligence with scalability and ethics both at the forefront. Its AI Principles were established in 2017 to guide AI development, and Google regularly releases reports about how they’re putting those principles to work in their latest releases and product updates.

Pros and cons

Pros Cons
Integration with Google Search and apps. Image output concerns and issues.
Comprehensive quality management features. Some issues with logical outputs and query responses.

Pricing

  • Gemini: Free.
  • Gemini Advanced: Available through Google One AI Premium subscription, which is $19.99 per month after a two-month free trial.
  • Business add-on for Google Workspace: Starting at $20 per user per month, billed annually.
  • Gemini Enterprise for Google Workspace: Starting at $30 per user per month, billed annually.
  • Gemini 1.0 Pro API: Free through Google AI Studio for up to 60 queries.

Features

  • AI Principles guiding product research and development.
  • Gemini 1.0 in three different sizes: Ultra, Pro, and Nano.
  • Google Search and widgets to support content outputs.
  • Multimodal inputs and outputs with fact-checking capabilities.
  • Mobile version for iOS and Android users.

Amazon Web Services icon.

Amazon (AWS)

Best for generative AI as a service

  • Headquarters: Seattle, WA, USA
  • Founded: 1994
  • Company Size: 1.5 million+ employees
  • Key Products: Amazon Bedrock, Amazon Q, Amazon CodeWhisperer, Amazon SageMaker
  • Market Cap: $1.79 trillion

AWS not only develops several advanced generative AI solutions but also offers its customers various managed services so they can access existing foundation models, build their own foundation models, and benefit from other generative AI solutions and use cases, depending on business need.

SageMaker is a great solution for users who want to start from scratch, while Bedrock offers managed access and support for users who want to customize third-party models like Anthropic’s Claude, Cohere’s Command and Embed, Stability AI’s Stable Diffusion, and Meta’s Llama 2.

AWS’s customers for generative AI range from small startups to major enterprises and brands like Intuit, Nasdaq, Adidas, and GoDaddy. In addition to its managed services and knowledgeable in-house support specialists, customers can benefit from a diverse partner network and the AWS Marketplace.

Pros and cons

Pros Cons
Fully managed generative AI service options. Complicated pricing approach.
AWS Free Tier for experimentation. Pricing can quickly get expensive.

Pricing

Pricing for Amazon’s generative AI solutions is highly variable. While most organizations will need SaaS, managed services, usage-based, and other pricing models that can get expensive, it’s important to know that several of these solutions can be used in limited ways through the AWS Free Tier.

  • Amazon Bedrock: Pricing dependent on provider, model, and selected modality. Learn more about the specifics here.
  • Amazon SageMaker: Pricing is highly customizable for this product. Learn more here.
  • Amazon Q: Between $20 and $25 per user per month, depending on selected plan.
  • Amazon CodeWhisperer: Free individual plan; $19 per user per month for Professional plan.

Features

  • Access to third-party models through Amazon Bedrock.
  • Foundation model building via Amazon SageMaker.
  • PartyRock playground for Amazon Bedrock.
  • Proof of concept development through Generative AI Innovation Center.
  • Amazon Q and CodeWhisperer applications for user-experience tasks.

To gain a deeper understanding of the AI app sector, read our guide to Best AI Apps for Mobile.

Nvidia icon.

NVIDIA

Best generative AI infrastructure and hardware provider

  • Headquarters: Santa Clara, CA, USA
  • Founded: 1993
  • Company Size: 29,000+ employees
  • Key Products: NVIDIA AI, NVIDIA NeMo, NVIDIA BioNeMo, NVIDIA Picasso, various chips and GPUs
  • Market Cap: $2.14 trillion

NVIDIA is one of the top providers of the hardware necessary to power large-scale generative AI models on the market today. It offers dozens of GPU options that work for different memory configurations, boost clock speed, and other requirements. Additionally, it has further democratized generative AI access with recent hardware and computer releases, including new RTC-powered PCs and workstations.

Although NVIDIA is best known for the hardware and software infrastructure solutions it supplies to the AI market, it also offers several of its own generative AI solutions to users. These include NeMo and BioNeMo, both of which give users a cloud-native framework to develop and deploy generative AI models according to their specifications.

Pros and cons

Pros Cons
A leading producer of GPUs and compute resources for generative AI. Some performance issues with lower-level GPUs.
Frequent innovations in GPU, hardware, and software solutions. Steep learning curve for NVIDIA products.

Pricing

Through NVIDIA, users can purchase several different types of GPUs and other hardware that can be used for generative AI compute and processing power. The vendor also offers subscriptions to several of its own generative AI tools. We’ve covered pricing for some of the most popular solutions below:

  • NVIDIA GeForce RTX GPUs: Pricing ranges between $399 and $1,599.
  • NeMo: Free, open-source access through GitHub; free container access via NVIDIA NGC; pricing information available upon request for NVIDIA AI Enterprise.
  • NVIDIA LaunchPad: Various free, hands-on labs.
  • BioNeMo: Free access to BioNeMo Framework Training; Beta application process for Cloud APIs access.

Features

  • LaunchPad for access to free hands-on lab environments.
  • Generative-AI-ready laptops and desktops.
  • Dozens of generative-AI-level GPUs and other hardware solutions.
  • NeMo, BioNeMo, Picasso, and ACE models and foundries.
  • DGX and Certified Systems accelerated infrastructure.

Anthropic icon.

Anthropic

Best for generative AI safety and explainability

  • Headquarters: San Francisco, CA, USA
  • Founded: 2021
  • Company Size: 50-300 employees
  • Key Products: Claude 3, Claude API
  • Market Cap: Private company valued at $15 billion

Anthropic is a leading generative AI startup that believes quality and safety should take precedence over quantity and speed, though it’s important to note that this vendor offers one of the largest context windows on the scene of generative AI models and chatbots. Its team is made up of AI researchers and engineers but also policy experts, business leaders, and stakeholders from across government, academic, nonprofit, and industrial backgrounds.

Anthropic’s flagship product is Claude, an AI assistant that focuses on high-quality content generation, summarization, and explanations. Claude is highly customizable and can be used for workflow automation, natural language conversation, text processing, and Q&A. Its capabilities and quality have also grown with the recent release of Claude 3.

Pros and cons

Pros Cons
Focused on transparent, explainable AI research and development. Expensive per-token pricing for Claude 3.
Claude balances utility with appropriate/inoffensive responses. Claude cannot access the internet.

Pricing

The Claude versions listed below are the most popular today. Users can also find legacy model pricing information here.

  • claude.ai: Free online access.
  • Build plan: API access appears to be free; this plan offers access to all Claude model versions.
  • Scale plan: Pricing available upon request; this plan offers access to all Claude model versions.
  • Claude 3 Haiku: $0.25 per 1 million input tokens and $1.25 per 1 million output tokens.
  • Claude 3 Sonnet: $3 per 1 million input tokens and $15 per 1 million output tokens.
  • Claude 3 Opus: $15 per 1 million input tokens and $75 per 1 million output tokens.

Features

  • Extensive AI research library.
  • Free, multimodal content generation via claude.ai.
  • API access for multiple Claude versions.
  • Three Claude 3 versions: Haiku, Sonnet, and Opus.
  • 200k context window.

Cohere icon.

Cohere

Best for natural language processing

  • Headquarters: Toronto, ON, Canada
  • Founded: 2019
  • Company Size: 50-300 employees
  • Key Products: Command, Embed, Chat, Generate, Semantic Search
  • Market Cap: Private company valued at $2.2 billion

Cohere offers a variety of high-powered natural language processing tools for text retrieval, classification, and generation. Its approach to large language models is comprehensive, not only giving users the ability to generate new content but also to search and summarize large sets of pre-written content. With a user-friendly API, app integrations, and quickstart guides, Cohere makes it possible and encourages companies to customize Cohere products to meet their own requirements.

Cohere’s main models are Command, Embed, and Rerank. These power various capabilities and purpose built solutions: Chat, Summarize, Generate, Embeddings, Semantic Search, and Classify.

Pros and cons

Pros Cons
Cohere Playground available for model and parameter testing. Limited models available for fine-tuning.
Easy-to-use APIs. Some bugginess and inaccuracies in outputs.

Pricing

Below, we’ve covered pricing information for some of Cohere’s most popular products. You can find additional pricing information here.

  • Playground: Free, rate limited usage for prototyping and pre-production work.
  • Chat: Between $0.30 and $0.50 per 1 million input tokens, $0.60 and $1.50 per 1 million output tokens, and $1.00 per million training tokens.
  • Summarize: $1 per 1 million input tokens and $2 per 1 million output tokens.
  • Embed: $0.10 per 1 million tokens.
  • Classify: $0.05 per 1,000 classifications.
  • Rerank: $1 per 1,000 searches.

Features

  • Three models: Command, Embed, and Rerank.
  • Default and fine-tuning models for certain products.
  • Cohere Playground.
  • LLM University, Documentation, and Quickstart Guides.
  • Deployment through Cohere API or Amazon SageMaker.

Glean icon.

Glean

Best for workplace search and knowledge management

  • Headquarters: Palo Alto, CA, USA
  • Founded: 2019
  • Company Size: 200-500 employees
  • Key Products: Glean, Glean Chat, Glean Assistant
  • Market Cap: Private company valued at $2.2 billion

Glean offers generative AI-powered internal search for workplace apps and ecosystems that meets the needs of both business leaders and employees. Companies across different industries and backgrounds use Glean to make it easier for employees to search for company knowledge and contextualize that information to their roles.

The way Glean is designed, each company has its own dynamic knowledge graph that learns and adapts to specific people, interactions, and content requests. Most recently, the company has also upped its retrieval augmented generation (RAG) approach. Through these innovations, everyone from your engineering team to your sales team can use Glean to find the up-to-date information they need more quickly and easily. Other key features that make this a highly usable tool include:

  • Verified answers: Save and verify answers to frequently asked questions.
  • Curated collections: The ability for individual teams to collect and organize documents and links that are most relevant for their team; ideal for onboarding.
  • GoLinks: Short links that can be created and saved for your most commonly used resources.

Pros and cons

Pros Cons
Internal search that balances security and usability. Little pricing transparency.
Semantic understanding for personalization opportunities. Some customer support limitations.

Pricing

Pricing information for Glean is available upon request. A demo is also available.

Features

  • Knowledge graph focused on internal content, people, and communications.
  • Retrieval augmented generation process.
  • 100+ connectors.
  • Semantic understanding in personalized searches.
  • Verified answers and GoLinks.

Jasper icon.

Jasper

Best for social media and digital marketing content generation

  • Headquarters: Austin, TX, USA
  • Founded: 2020
  • Company Size: 50-200 employees
  • Key Products: Jasper, Jasper API, Jasper AI Copilot
  • Market Cap: Private company valued at $1.2 billion

Jasper is a leading generative AI writing tool, and is a favorite for marketers and content creators. It offers features to support blog and email writing, SEO optimization, and art and ad imagery creation. It’s easy to use and access, with both Chrome and Microsoft Edge extensions and the Jasper API.

Jasper has always had a business bent with its focus on marketer-style content, but in February 2023, the company took it to a new level with its announcement of Jasper for Business, which increased its customizable brand voice features and tools.

Its next biggest innovation came in the form of Jasper AI Copilot, which offers more hands-on support for AI-generated content, company knowledge management, and data analytics and insights. Most recently, Jasper has also increased its multimodality and generative AI image generation capabilities through the acquisition of Clipdrop.

Pros and cons

Pros Cons
Customizable templates and prompts for branding. Limited features in lower-tier plans.
Easy-to-use browser extensions. Pricey compared to similar tools.

Pricing

  • Creator: $39 per user per month, billed annually, or $49 per user billed monthly.
  • Pro: $59 per user per month, billed annually, or $69 per user billed monthly.
  • Business: Pricing information available upon request.

Features

  • 50+ AI templates.
  • Jasper AI Copilot.
  • Jasper Everywhere browser extensions.
  • Brand voice library and management.
  • Accessible, branded chat interface.

Hugging Face icon.

Hugging Face

Best for community-driven generative AI development

  • Headquarters: Brooklyn, NY, USA
  • Founded: 2016
  • Company Size: 100-300 employees
  • Key Products: BLOOM, AutoTrain, Inference Endpoints
  • Market Cap: Private company valued at $4.5 billion

Hugging Face is a community-driven developer forum for AI and machine learning model development initiatives. Its wide variety of prediction models and datasets makes it possible for organizations to custom-build their own generative AI solutions and other AI toolsets.

Many major enterprises and generative AI startups work on Hugging Face to optimize existing AI models and develop new ones from scratch. Although the forum is designed with developers and programmers in mind, certain Hugging Face solutions, like AutoTrain, require little to no coding. Others, like BLOOM, also offer different levels of accessibility as well as the ability to generate content in a variety of human and computer languages. While quality is questionable on some of the rarer languages included, it has some of the widest multilingual coverage on the market today.

Pros and cons

Pros Cons
Open-source, collaborative development environment. Less friendly to non-technical users.
Embeddable generative AI technology for affordable scalability. Limited governance over third-party development tools, like Stable Diffusion.

Pricing

  • Hugging Face Hub: Free.
  • Pro Account: $9 per month.
  • Enterprise Hub: Starting at $20 per user per month.
  • Spaces Hardware: Starting at $0.05 per hour.
  • Inference Endpoints: Starting at $0.06 per hour.

Features

  • Community-driven support and resources.
  • BLOOM for multilingual content generation: 46 languages and 13 programming languages.
  • Access to most LLMs.
  • Text generation and logical text completion.
  • Learned subword tokenizer.

Inflection AI icon.

Inflection AI

Best for conversational AI technology

  • Headquarters: Palo Alto, CA, USA
  • Founded: 2022
  • Company Size: Less than 100 employees
  • Key Products: Pi, Conversational API, Inflection-2.5
  • Market Cap: Private company valued at $4 billion

Inflection AI earned a formidable reputation long before it released any products simply due to the pedigree of its founders: Mustafa Suleyman, a co-founder of DeepMind and former VP of AI products and AI policy at Google; REid Hoffman, a co-founder of LinkedIn and former EVP at PayPal; and Karén Simonyan, former principal scientist at DeepMind. Unlike many of the other players in this list, Inflection AI is more focused on narrow, purpose-built generative AI solutions rather than AGI. This is evident through Pi, its “personal AI” that focuses on empathetic, conversational AI with humans.

Though Pi is still more focused on conversational AI and personal usage, the recent release of Inflection-2.5 has increased its capabilities for more technical queries and can now provide results based on real-time web searches.

While testing out these new features, I received comprehensive and accurate responses for the most part. However, when I asked Pi how its performance compares against Google’s Gemini, it told me it didn’t know of a Google product by that name. Expect to see more improvements as this new addition to the tool was only released very recently.

Pros and cons

Pros Cons
User-friendly mobile access. No multimodal outputs beyond text and voice.
Founded by former leaders from DeepMind, Google, and LinkedIn. Some knowledge limitations, though Pi can now access the web.

Pricing

Pi is free to use.

Features

  • Pi app on iOS and Android devices.
  • Pi available through WhatsApp, Instagram, Telegram, and Facebook.
  • Focused R&D on advanced applied AI over artificial general intelligence (AGI).
  • Inflection-2.5 in-house model.
  • pi.ai online version.

Adobe icon.

Adobe

Best generative AI creative suite

  • Headquarters: San Jose, CA, USA
  • Founded: 1982
  • Company Size: 29,000+ employees
  • Key Products: Adobe Sensei, Adobe Firefly, AI Assistant
  • Market Cap: $253.62 billion

Adobe has long been the leader for creative software suites, offering tools that support graphic design, video creation, photo editing, and other creative tasks for personal and business projects. Adobe has jumped into generative AI in a significant way, offering generative AI capabilities directly to its users in both the Creative Cloud and Experience Cloud, meaning users can benefit from generative AI assistance and capabilities while creating marketing content and while managing customer experiences.

Adobe’s main generative AI solutions at this time are Sensei and Firefly. Sensei primarily works in Experience Cloud, helping users with AI-powered forecasting and analytics, asset intelligence, personalized commerce experiences, customer journey management and automation, and more. Adobe Firefly is offered through Creative Cloud, giving users the ability to generate images with text prompts, fill and recolor images, and create text effects. Depending on the tool you’re using, Adobe’s generative AI can also support quick content summarization tasks.

Pros and cons

Pros Cons
Deep AI integration with Adobe Creative Cloud and Adobe Experience Cloud. Some limitations on generative credits in Creative Cloud plans.
Innovative research in image and multimedia editing. Occasional inaccuracies in generated images; missing key prompt details.

Pricing

  • Adobe Sensei: Sensei is included with each Adobe Experience Cloud product. You can find pricing for these products here.
  • Adobe Firefly: Limited, free version.
  • Adobe Firefly Premium Plan: Starting at $4.99 per month.
  • Adobe Express Premium Plan: Starting at $9.99 per month.
  • Adobe Creative Cloud: Generative credits and add-ons are available for several Adobe Creative Cloud products. You can find more specific pricing information here.

Features

  • Adobe Sensei for marketing workflow, customer journey, and analytics support.
  • Adobe Firefly for AI-powered image and photo generation and effects.
  • Content Authenticity INitiative and Coalition for Content Provenance and Authenticity.
  • Adobe Acrobat Assistant and Generative Summary in beta.
  • Personal and business use access to generative credits.

IBM icon.

IBM

Best for AI and data governance

  • Headquarters: Armonk, NY, USA
  • Founded: 1911
  • Company Size: 280,000+ employees
  • Key Products: watsonx.ai, Code Assistant, Slate, Granite
  • Market Cap: $175.77 billion

IBM is an established tech enterprise in virtually all categories, now including generative AI. Its Watsonx family of generative AI assistive tools and features is an asset for both data and AI model lifecycle management, as each version of the watsonx tool focuses on a key area of AI development: AI governance, data management, and orchestration, for example.

With Watsonx.governance, users can monitor and govern IBM generative AI models as well as models in third-party platforms like Amazon Bedrock, OpenAI’s platforms, and Microsoft Azure. Compliance, risk management, and lifecycle governance are core parts of this framework, which includes a focus on driving AI explainability through detailed model factsheets.

Pros and cons

Pros Cons
Extensive AI and data governance assistance through watsonx. Steep learning curve for some users.
Helpful CEO guides for how to use generative AI. Complex pricing structure with limited transparency.

Pricing

Pricing for IBM Watsonx products is available through SaaS tiers and individual software solution pricing. We’ve covered the basics below, but you can find more pricing information here.

  • SaaS Essentials: $0 per month plus per-hour node and services access and $0.60 per resource unit used in watsonx.governance.
  • SaaS Standard: $1,050 per month plus per-hour node and services access; no watsonx.governance is available for this plan at this time.
  • watsonx Assistant: $0 for Lite, starting at $140 per month for Plus, and custom pricing for Enterprise.
  • Per-product pricing: Varies.

Features

  • Watsonx.ai for content generation, classification, summarization, extractions, and Q&A modeling.
  • Watsonx.data for AI and data workload management.
  • Watsonx.governance AI workflow and development management with transparency and explainability focus.
  • Watsonx Assistant for real-time customer assistance tasks.
  • Watsonx Code Assistant for code generation assistance.

C3 AI icon.

C3.ai

Best for enterprise generative AI application development

  • Headquarters: Redwood City, CA, USA
  • Founded: 2009
  • Company Size: 500-2,000 employees
  • Key Products: C3 AI Platform, C3 Generative AI, C3 AI Pilot
  • Market Cap: $3.77 billion

C3.ai is a leading solutions provider for enterprise generative AI, offering prebuilt solutions and tools to custom-build LLM-agnostic, enterprise AI applications in major cloud ecosystems. Though virtually any business could partner with C3.ai to develop an application that addresses their business’s pain points, C3.ai focuses primarily in manufacturing, utilities, oil and gas, financial services, government, defense and intelligence, healthcare, retail, transportation, and telecommunications.

The company offers prebuilt suites of tools for various industries and business use cases, including CRM, reliability, sustainability, supply chain, and financial services management. For any solutions you need that aren’t already covered, you can use the C3 AI Platform to build and C3 AI Pilot to support a streamlined app deployment process in approximately six months.

Pros and cons

Pros Cons
App development and tools for specific enterprise use cases. Some volatility in market cap and valuation over time.
Strong industry and manufacturing experience. High upfront investment costs.

Pricing

Generally speaking, C3 Generative AI application development and licensing costs $250,000 for 12 weeks of production plus additional costs per vCPU or vGPU used per hour after that point. Pricing may also depend on which cloud you purchase from:

  • C3 Generative AI in Google Cloud: $83,333.33 per month; no usage fee charged here.
  • C3 Generative AI: Production Pilot in AWS: $250,000 for three months.
  • C3 Generative AI: Production Pilot in Microsoft Azure: $250,000 for three months plus on-demand $0.55 per vCPU or vGPU hour.

Features

  • C3 AI Pilot.
  • C3 AI Platform available via AWS, Azure, and Google Cloud.
  • Search and chat interface for enterprise knowledge management.
  • Industry-specific and business-process-specific versions of C3 Generative AI.
  • C3 Generative AI designed specifically for Databricks, Dynamics 365, Oracle ERP, Oracle Netsuite, Palantir, Salesforce, SAP, ServiceNow, Snowflake, and Workday.

Meta icon.

Meta

Best for generative AI cybersecurity

  • Headquarters: Menlo Park, CA, USA
  • Founded: 2004
  • Company Size: 67,000+ employees
  • Key Products: Meta AI, Llama 2, Llama 3 (coming soon), Seamless Communication models
  • Market Cap: $1.23 trillion

Meta, the parent company of Facebook, has forged a creative path forward in the generative AI landscape, focusing first and foremost on ethical AI development and developing free, open-source models that can work on consumer-grade hardware without major performance issues. In recent months, it has expanded its focus to Meta AI, an AI assistant and solution that works directly in Meta apps like Facebook, Instagram, and WhatsApp to support image generation and other creative content tasks.

But where Meta really shines is in its commitment to privacy and security. At the end of 2023, the company announced Purple Llama, a project with open trust and safety tools, the company’s Responsible Use Guide, and CyberSec Eval, which includes detailed cybersecurity safety evaluation benchmarks for generative AI models. The company has also released Llama Guard, a safety classifier that controls input and output quality without impacting deployment or performance.

Pros and cons

Pros Cons
Access to free, consumer-grade, open-source solutions. Some model parameter and performance limitations.
Purple Llama for increased generative AI security. Learning curve for open-source models.

Pricing

Most generative AI solutions from Meta are free and open source.

Features

  • AI Research and AI Resources libraries.
  • Purple Llama for developer-driven security.
  • Llama open platform for AI modeling.
  • Meta AI image generation with responsible AI labeling.
  • Meta AI messaging in Instagram, Facebook Messenger, and WhatsApp.

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Databricks

Best for large-scale data preparation for AI projects

  • Headquarters: San Francisco, CA, USA
  • Founded: 2013
  • Company Size: 1,000-3,000 employees
  • Key Products: Mosaic AI, Data Intelligence Platform, Unity Catalog, Vector Search, Data Lakehouse Platform
  • Market Cap: Private company valued at $43 billion

Databricks is one of the fastest-growing tech companies in the world today, and while its focus is on big data and the full lifecycle of data management, this specialization naturally has led to innovations in generative AI.

Through Mosaic AI, which is built on the Data Intelligence Platform, users can build LLMs and predictive models alike in an environment where they own and have complete control over the data going into these models. Users can build models in Mosaic AI through prompt engineering, retrieval augmented generation (RAG), fine-tuning an existing model, or pretraining a new model.

Beyond Mosaic AI, users can actually prepare their data for generative AI projects through solutions like the Data Lakehouse Platform. Lakehouse Monitoring is a particularly useful solution, helping customers to automate quality checks for the outputs that come from the models they develop.

Pros and cons

Pros Cons
Various governance, discovery, and versioning capabilities in all-in-one solution. DBU-based pricing can get expensive for large workloads and projects.
Databricks Lakehouse Monitoring for data and model quality management and predictions. More technical data management solution with steeper learning curve.

Pricing

Pricing for Databricks is highly variable and based on which plan you select, which cloud you select, which region you live in, the platform tier you select, and other factors. For limited use cases, the Databricks community version offers free access.

In general, Databricks follows DBU-based pricing — based on custom Databricks Units of usage — for several specialty tools and workloads. To figure out exactly how much Databricks generative AI solutions will cost for your organization, you can learn more about their pricing options here.

Features

  • Mosaic AI for generative AI model training and deployment.
  • AI model governance.
  • Data management and warehousing tools.
  • Model Serving for model governance, querying, and deployment.
  • Unity Catalog for asset monitoring and quality management.

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Stability AI

Best multimedia foundation models

  • Headquarters: London, England, UK
  • Founded: 2019
  • Company Size: 50-200 employees
  • Key Products: Stable Diffusion XL, Stable Video Diffusion, Stable Audio, Stable Zero123
  • Market Cap: Private company valued at $1 billion

Stability AI is the engine that powers many of the latest and greatest generative AI solutions. The company’s deep learning model, Stable Diffusion, offers open-source code — primarily via GitHub and Hugging Face — that several other companies have opted to build off of for image and AI video generation. The company also offers an extensive API library that third-party users can take advantage of, and a Discord community where users can discuss how they use Stable Diffusion technology.

In addition to the Stable Diffusion family of image generation models, Stability AI has developed dedicated models for generating content in other mediums: Stable Video Diffusion for video content creation, Stable Audio for music and sound effect creation, Stable Zero123 for 3D object generation, and several specialized language models for different types of text content generation. While the company has faced controversy for its image-sourcing practices, and there’s also talk of profitability problems in the organization, so far they have managed to stay afloat and maintain a loyal customer base.

Pros and cons

Pros Cons
Open-source accessibility and customizability. High spending on foundational technology has hurt profitability for the company.
Wide variety of mediums covered in models, including 3D object generation. Controversies over personal data allegedly used without permission.

Pricing

Many Stability AI capabilities are free and open source. Stability AI memberships are priced as follows:

  • Non-Commercial: $0 for personal use and research.
  • Professional: $20 per month for creators and developers with less than $1 million in revenue, $1 million in institutional funding, and 1 million monthly active users.
  • Enterprise: Pricing information available upon request.

Features

  • Self-hosted, platform API, and cloud platform deployment options.
  • Stable Diffusion XL and Turbo, both in English and Japanese.
  • Stable Video Diffusion.
  • Stable Zero123 for 3D object generation.
  • Stable Audio for music and sound effect generation.

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Synthesia

Best generative AI video company

  • Headquarters: London, England, UK
  • Founded: 2017
  • Company Size: 200-500 employees
  • Key Products: Synthesia
  • Market Cap: Private company valued at $1 billion

Synthesia is a leading AI video generation company that helps businesses to create high-quality video content for digital marketing, training, and other use cases that have traditionally required video equipment and editing expertise.

With Synthesia, there’s no need to even pay real actors: abundant AI avatars, languages, and voices are available to help bring video ideas to life with minimal upfront effort. And for users who aren’t happy with the preexisting avatar options, there’s also a feature that allows them to create their own avatars.

Synthesia’s customers consistently praise the quality of the content it produces, with special compliments paid to the quality of AI avatars and how human they look. Major enterprises, including Microsoft, Zoom, Accenture, Reuters, Xerox, Johnson and Johnson, and Heineken are among its customers.

Pros and cons

Pros Cons
High-quality AI avatars and 120+ stock languages. Authoring environment bugs.
Ease of use. Some audio and speech quality issues.

Pricing

  • Starter: $22 per month, billed annually, or $29 billed monthly.
  • Creator: $67 per month, billed annually, or $89 billed monthly.
  • Enterprise: Pricing information available upon request.

Features

  • 140+ AI avatar options.
  • 120+ languages and voices.
  • AI video assistant.
  • 60+ video templates.
  • Various sharing and export options.

To learn about today’s top generative AI tools for the video market, see our guide: 5 Best AI Video Generators.

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Grammarly

Best for integrated writing assistance

  • Headquarters: San Francisco, CA, USA
  • Founded: 2009
  • Company Size: 1,000-3,000 employees
  • Key Products: Grammarly
  • Market Cap: Private company valued at $13 billion

Grammarly has been a staple writing and grammar tool for many years, and with the generative AI capabilities it is now a leading AI writing tool. This advance has more firmly established the company’s utility among business users for a variety of writing projects and tasks.

In the free version of Grammarly, users can easily push the generative AI button and use it to rewrite existing content, evaluate existing content for current gaps, and more. The paid tool takes things a step further, giving users access to more monthly prompts, advanced writing suggestions, and team collaboration capabilities.

Part of why Grammarly’s generative AI is so useful is because it’s easy to access across a variety of tools. If you’ve added the free Grammarly extension to your browser, without any additional effort, you can access the Grammarly icon and its generative AI capabilities directly in the search bars and app interfaces of tools like ChatGPT, Google Docs, Gmail, LinkedIn, and other locations where professionals do most of their writing.

Pros and cons

Pros Cons
Generative AI available in paid and free plans. Narrow focus and use cases.
Custom content generation in third-party business tools, like Google Docs and ChatGPT. Occasional response lags and other bugs.

Pricing

  • Free: $0 for limited features.
  • Premium: $12 per month, billed annually, or $30 billed monthly.
  • Business: $15 per user per month, billed annually, or $25 per user billed monthly.
  • Enterprise: Pricing information available upon request.

Features

  • Trust Center for explainable and transparent AI practices.
  • Limited generative AI prompting and assistance in free tool.
  • In-app content suggestions and rewriting for tools like Google Docs, LinkedIn, Gmail, and ChatGPT.
  • Rephrase and rewrite buttons.
  • Plagiarism tracking and identification in paid plans.

To see a full list of apps that can you help you create text for your projects, see our guide: Best AI Writing Tools.

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MOSTLY AI

Best for synthetic data generation

  • Headquarters: Vienna, Wien, Austria
  • Founded: 2017
  • Company Size: 50-200 employees
  • Key Products: Mostly AI, API
  • Market Cap: Private company with unknown valuation

MOSTLY AI is one of the top synthetic data generation companies today, supporting users in generating new, usable data that works for product design and development, test data generation, and AI and ML development projects. Many customers turn to MOSTLY AI because of its commitment to data security and privacy best practices, including data anonymization, model overfitting prevention, random draw synthesis, and regulation-specific compliance certifications and standards.

Depending on the plan selected, users can benefit from multiple deployment options — including on-premises deployment and private cloud deployment, user authentication options, and other customizations. While user reviews indicate that the tool is easy to use and consistently produces high-quality synthetic data, these same reviews reveal that customers would appreciate if MOSTLY AI offered more explainability for its outputs.

Pros and cons

Pros Cons
Low-code/no-code synthetic data generation. Limited information available about company valuation and future plans.
Highly capable and useful free version. Limited elasticity when usage requirements change.

Pricing

  • Free: $0 for five daily credits.
  • Team: $3 per credit, with credits applied based on concurrent jobs, creators, and synthetic data generated.
  • Enterprise: $5 per credit, with credits applied based on concurrent jobs, creators, and synthetic data generated.

Features

  • Time-series and structured data support.
  • Data insights reports.
  • Smart imputation and data rebalancing.
  • Temperature control for fine-tuning.
  • Multiple deployment, integration, and connector options.

Key Features of Generative AI Companies

Generative AI companies are all working on different AI software and for different audiences, but at their core, the best generative AI companies all share the following features and characteristics:

Extensive R&D Pipelines and Products

Research and development is especially important to generative AI right now as the technology is still relatively new and potential AI use cases may still be unrealized. The top generative AI companies all have large teams focused on research and development, not only for their current and proposed projects, but also for generative AI technology, explainability, and transparency as a whole.

This type of research helps them to prepare high-quality products for commercial use while also outperforming competitors to specific use cases.

Explainability and Transparency

Though current AI governance and ethics laws around the globe are limited, customers are demanding that generative AI companies share how they collect data, how they train models, and how models arrive at the solutions they produce. Explainability and transparency are at the forefront of generative AI innovation right now, especially as businesses gear up for impending legislation like the EU AI Act.

Ethical Approaches to Privacy and Security

As more and more businesses use generative AI solutions to support their daily work, more enterprise data and sensitive IP is coming into these systems. That’s why customers prefer working with generative AI companies that offer built-in privacy and security management features as well as transparent explanations of how data is used, stored, and protected throughout the AI lifecycle.

Solutions Portfolio for Innovative Enterprise Use Cases

The top generative AI companies provide users with multiple tools or resources that explain how to use their solutions to simplify various enterprise tasks and workflows.

In some cases, generative AI companies are beginning to build industry-specific versions of their solutions to cater to large markets that are particularly interested in generative-AI powered automations, analytics, and content generation.

Scalable High-Performance Computing Infrastructure

Whether they’re developing their own or making a major investment in supplies from a computing hardware and infrastructure solutions provider, the top generative AI companies need to invest in scalable hardware, software, and other resources to train and deploy LLMs. To do the kind of work these models do quickly and at scale requires large amounts of compute power for high performance. The top generative AI companies ensure they have what they need to meet performance criteria for hundreds or thousands of customers simultaneously.

How to Choose the Best Generative AI Companies for Your Business

Partnering with a generative AI company or selecting one of their product subscriptions is a big decision that may be costly or resource-intensive for your organization. Before choosing the generative AI companies that you want to work with, it’s important to first assess your business’s generative AI requirements, budget, and any relevant in-house skills or resources that will help or deter your ability to work with this kind of technology.

Knowing upfront who you’re dealing with and what you need from them will help you to find a partner that offers the right technologies as well as the support access and supplementary resources you need to get started and continue smoothly with any generative AI operations you choose to pursue.

Frequently Asked Questions (FAQs)

Learn more about the top generative AI companies and the products they’re creating through these frequently asked questions:

What are the top generative AI models?

The top generative AI models right now are GPT-3 and GPT-4, Gemini, Claude, DALL-E 3, Stable Diffusion, Llama 2, Jurassic-2, and BLOOM. A variety of other popular and high-quality generative AI models are available for text, audio, image, video, and other types of content generation, too.

Who are the key players in generative AI?

The key players in generative AI are innovative generative AI startups like OpenAI, Anthropic, Cohere, Glean, Jasper, and Hugging Face, as well as major tech companies and established leaders like Microsoft Alphabet (Google), AWS, and NVIDIA. Beyond the players covered in this guide, other leaders include AI21 Labs, Midjourney, Notion, GitHub, and Tabnine.

How are big companies using generative AI?

Big companies are using generative AI to automate and streamline their processes, create purpose-built tools to handle routine or complex taskwork, and generate new content for product launches, marketing, and more at scale. Learn more about generative AI’s enterprise use cases here.

How does generative AI work?

Generative AI technology is typically designed with neural network algorithms that mimic the design and behavior of a human brain. With that setup, generative AI models are given massive training datasets to analyze and use as their knowledge base when generating new content.

The amount and variety of training data that go into these neural networks make it so generative AI tools can effectively learn data patterns and contextual relationships, then apply that knowledge to the content they create. The success of a generative AI solution is based heavily on the quantity, quality, variety, and neutrality of the training data it’s fed.

For a deeper understanding of two key AI topics, read our guide: Generative AI vs. Predictive AI: What’s the Difference?

Who is investing in generative AI?

Big tech companies like Microsoft, Google, and AWS are investing in generative AI startups and technology. For example, Microsoft is one of the biggest investors in OpenAI. Many of these companies have already developed their own generative AI tools and operations as well.

Bottom Line: Reviewing the Top Generative AI Companies

Generative AI companies offer compelling AI technology not only to technical users and developers but also to the everyday consumer. The generative AI companies in this list have put forth some of the most interesting generative AI tools and use cases to date and are worth watching if you’re keeping an eye on the future of AI technology.

Some of these companies have had a meteoric launch, releasing several different products and generating millions of dollars in funding. On the other hand, a few of these organizations have taken a slower and steadier approach, first focusing on their idea and the ethics and safety behind development before going all in on a product launch. In all of these cases, the top generative AI companies are creating solutions that have the potential to scale with business and private user expectations in the long run.

For a detailed list of today’s leading generative AI apps, see our guide: Top 20 Generative AI Tools & Applications.

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