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ADOBE COLDFUSION FEATURES

AI Driven Development

ColdFusion delivers a modular framework for building intelligent applications that connect large language models, enterprise data, and business workflows. With native AI integrations, document processing pipelines, RAG capabilities, MCP interoperability, and vector database support, ColdFusion simplifies the development of modern AI-driven applications while maintaining enterprise-grade reliability and security.

See it in action | See it in action ADOBE COLDFUSION FEATURES

https://main--da-cc--adobecom.aem.page/cc-shared/fragments/products/coldfusion/feature5#play | Seamless AI Model Integration | :play-medium:

Seamless AI Model Integration

Enable faster delivery of enterprise AI experiences with simplified model integration, flexible deployment, secure connectivity, and scalable real-time interactions across applications.

  • LLM Connectivity: Integrate with leading models from Anthropic, OpenAI, Google Gemini, and Mistral AI.
  • Flexible Model Deployment: Use hosted AI services when you need scale, or run models locally through tools like Ollama, private inference servers, or embedded in-process execution.
  • Embedding Support: Generate embeddings to enable semantic search, contextual retrieval, and intelligent recommendations.
  • Secure API Management: Built-in mechanisms for secure authentication and model access.
  • Streaming and Structured Responses: Support asynchronous streaming outputs and structured responses for real-time AI interactions.

Explore the Documentation | Watch the Full Tutorial

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Intelligent Document Processing

Accelerate enterprise AI workflows by simplifying document ingestion, improving retrieval accuracy, and enabling seamless transformation of unstructured content into AI-ready data within ColdFusion applications.

  • Unified Document Parsing: Extract and process information from multiple document formats through a single framework.
  • Automated Document Chunking: Split and structure content to optimize it for AI processing and retrieval.
  • Developer-Friendly Inspection: Return ColdFusion-native data structures for easier debugging and testing.
  • Pipeline-Ready Outputs: Feed processed documents directly into embedding, indexing, and AI workflows.

Explore the Documentation

https://main--da-cc--adobecom.aem.page/cc-shared/fragments/products/coldfusion/feature2#idp| Intelligent Document Processing | :idp-medium:
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https://main--da-cc--adobecom.aem.page/cc-shared/fragments/products/coldfusion/feature3#rag | RAG | :rag-medium:

Trusted Retrieval Augmented Generation (RAG)

ColdFusion enables rapid development of secure, scalable, context-aware AI applications using leading LLMs, built-in embeddings, and real-time AI interactions across cloud and on-premise environments.

  • Enterprise Knowledge Retrieval: Index and retrieve relevant information from documents and data sources.
  • Context-Aware Responses: Inject retrieved data into AI prompts to generate accurate, context-rich answers.
  • Asynchronous Processing: Scale retrieval and response generation across high-volume workloads.
  • Built-in Guardrails: Maintain control with safeguards that ensure reliable and safe AI responses.

Explore the Documentation | Watch the Full Tutorial

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MCP-Based AI Connectivity

Simplify integration with AI platforms by enabling ColdFusion applications to securely exchange data, trigger workflows, and power intelligent automation.

  • MCP Client Capabilities: Connect ColdFusion apps to external AI tools and models.
  • MCP Server Support: Expose application functions, workflows, and datasets to AI systems.
  • Bidirectional Integration: Enable two-way communication between ColdFusion services and AI platforms.
  • Workflow Orchestration: Participate seamlessly in larger AI automation pipelines.

Explore the Documentation | Watch the Full Tutorial

https://main--da-cc--adobecom.aem.page/cc-shared/fragments/products/coldfusion/feature4#mcp| MCP | :mcp-medium:
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https://main--da-cc--adobecom.aem.page/cc-shared/fragments/products/coldfusion/feature1#native| Native Vector Database Support | :native-medium:

Native Vector Database Support

Deliver more accurate and context-aware AI experiences by enabling intelligent search and retrieval across enterprise data using semantic understanding.

  • Vector Storage Integration: Store and query embeddings directly within ColdFusion-powered applications.
  • Semantic Search: Retrieve information based on meaning rather than keyword matching.
  • Similarity Matching: Discover related documents and data points across large datasets.
  • Embedding Integration: Connect embedding generation with vector storage for efficient AI retrieval.

Explore the Documentation | Watch the Full Tutorial

Questions? We have answers.

What is AI-driven development in ColdFusion?
AI-driven development in ColdFusion refers to using AI services and tools to accelerate application development, automate workflows, and build intelligent features into applications.
Can ColdFusion integrate with AI models like GPT or Gemini?
Yes. Adobe ColdFusion 2025 has built in, native support for a wide range of LLMs such as ChatGPT, Gemini, Claude, and others.
Is ColdFusion used to build AI models?
No. ColdFusion is not typically used to train AI models. Instead, it is used to integrate AI capabilities into applications, such as chatbots, recommendations, and automation workflows.
How does AI improve development in ColdFusion?

AI helps developers:

  • Automate repetitive tasks
  • Simplify integrations to reduce development effort and improve overall efficiency
  • Build smarter applications with less effort

AI-assisted tools can significantly improve productivity and reduce development time.

What kind of AI applications can be built with ColdFusion?
  • AI-powered chatbots
  • Intelligent search and recommendations
  • Automated workflows
  • Data-driven decision systems
Is AI integration in ColdFusion enterprise-ready?
Yes. ColdFusion supports secure API integrations and scalable architectures, making it suitable for enterprise AI applications.