Best AI Development Platforms 2025

What is an AI Development Platform?

AI Development Platforms enable businesses to develop, train, and fine-tune AI models. This includes generative AI models that create text, images, or videos in response to natural language prompts. Businesses also use AI Development Platforms to train other types of AI models that perform functions like image classification or search recommendation.

These platforms use machine learning, open source and proprietary tools, and secure integration into existing business data pipelines to train models. Businesses use these platforms to develop AI Chatbots for customer service or internal productivity. They can also create models that classify different types of data, for example, detecting fraud or segmenting customers, saving employees time and decision-making effort.

AI Development Platforms are related to Machine Learning Tools and Enterprise Generative AI Platforms. AI Development Platforms offer more features than Machine Learning Tools, including the ability to train and fine-tune existing models, integration with business data pipelines, and, often, a GUI so both developers and non-developers can use the platform. Enterprise Generative AI Platforms offer the same security focus and integrations with existing data as AI Development Platforms, but don’t offer the tools for users to develop and train their own models, only fine-tune existing models.

AI Development Platform Features

• Many models and frameworks: AI Development Platforms offer access to a variety of models and machine learning frameworks. Many popular platforms let businesses use and train over 100 different models.
• Data pipeline integration: A good AI Development Platform should integrate easily with a company’s data through APIs or connectors, allowing organizations to train models on company processes and internal knowledge.
• Managed scaling: AI models, particularly Generative AI models, require a lot of computing resources. These platforms have the necessary cloud computing and GPU resources available to scale up or down as needed automatically.
• Security and compliance: Sharing proprietary business data is often necessary for using and training AI models. AI Development Platforms offer security features like end-to-end encryption to ensure that data stays safe.

How to Choose an AI Development Platform

• Monitoring and Governance: A key strength and weakness of AI models is that there is a limit to how much you can control them. This is what allows them to function autonomously once trained, but it also means you want to maintain control over and visibility into that training process. Look for a platform that lets you monitor data ingested and produced by your models closely.
• Standalone platform or cloud service provider: The major cloud service providers, including Amazon, Microsoft, and Google, offer their own AI Development Platforms. If you’re already using one of these providers for most of your data and infrastructure needs, it may make integration easier to use their AI Development Platform as well. Standalone options are often cheaper and may offer access to a different set of models.
• Data management: Consider how much data you’ll be processing and whether the system has the storage, processing, and integration capabilities you need. In addition to APIs and connectors for integration, many platforms include hosted databases, data lakes, or data warehouses.
• Ease of use: AI Development Platforms are typically designed to provide a simpler starting point for model development than a machine learning framework alone. Consider who will be collaborating to use and develop the model and their level of technical expertise.

AI Development Platform Pricing Information

AI Development Platforms vary in their pricing structures. Some, including most large cloud service providers, use pay-as-you-go pricing, charging based on the compute power used. This charge is usually a couple of cents per pipeline execution, prompt run, and/or hour of usage. Others, including many standalone providers, charge a monthly rate instead, which can range from $10 to $500+. Enterprise companies will typically have to contact sales teams for custom quotes. Many platforms offer free tiers up to specific usage limits for those with lower computing requirements.

More Resources

• What is AIOps?
• Types of AI: Everything You Need to Know
• How Generative AI is Revolutionizing HR Practices
• Generative AI in the Software Buying Process