Enterprise Generative AI Platforms

What is Enterprise Generative AI?

Enterprise Generative AI platforms offer full-stack generative AI capabilities designed to integrate with enterprise data and applications. These platforms offer language models that can generate text, code, and images, like other generative AI tools. Enterprise Generative AI tools differentiate themselves by allowing for full integration with companies’ internal data and processes. Enterprise Generative AI models can be fine-tuned to better suit company voice, use case, and compliance standards. Vendors will also have options for retrieval augmented generation (RAG), which allows models to access and generate outputs based on enterprise data.

These platforms are used to automate and/or assist with a variety of repetitive business processes as well as create custom applications. The customizable nature of generative AI means that use cases are broad and include a variety of departments, from marketing to HR, and industries, from finance to healthcare.

Security, compliance, and governance are important factors for Enterprise Generative AI platforms. Enterprise-grade products offer greater control over how proprietary data is used. Some Enterprise Generative AI platforms include AI Governance tools. AI Governance features can help monitor generative AI outputs’ compliance with internal brand, compliance, and privacy standards.

Enterprise Generative AI Features

Most products in the Enterprise Generative AI category have the following features:

• Vendor-owned LLMs
• Text, image, and/or code generation
• Fine-tuning to account for company voice and other requirements
• Retrieval augmented generation (RAG), allowing models to access and use enterprise data
• API for integration and custom application building
• Usage analytics
• Customizable privacy, security, and compliance options

Enterprise Generative AI Comparison

When purchasing an Enterprise Generative AI platform, buyers should keep in mind:

• Compliance and Governance Requirements: Some vendors offer greater control over ensuring prompts and model outputs comply with brand, legal, and regulatory compliance than others. Consider your company’s compliance requirements, and whether or not you need or want a separate AI Governance tool.
• Technological Complexity vs. Customizability: While all Enterprise Generative AI platforms have APIs for integration and custom app building, some vendors offer more options for premade templates and prebuilt interfaces for prompting their models than others. Depending on your company’s use case, these plug-and-play options may or may not be desirable.
• Use Case: Some vendors offer models that are trained on specialized datasets and may be better suited for industry-specific use cases out of the box. Some vendors offer models that can generate only text, while others offer models that generate text, images, and code. Consider exactly how you hope to use Generative AI and what kind of training and capabilities you might benefit from.
• Accuracy: For enterprises and large scale deployments in particular, it is crucial that generative AI outputs accurately represent company data and policies. Compare how models have performed in common benchmark tests and what methods of knowledge retrieval each model uses. It is a good idea to test and evaluate a few top candidates directly - try a few fact- and/or retrieval-based prompts that are similar to how you plan on using the model.

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Pricing Information

Companies must contact vendors to obtain custom pricing quotes for Enterprise Generative AI platforms. Mid-tier pricing is generally based on usage, while enterprise pricing may take other factors such as number of users into account as well. Most vendors offer free and/or relatively cheap entry-level pricing for individual users or small teams.