AI & Machine Learning
AI & Machine Learning integrations for AI agents
Model providers, hosted inference endpoints, and ML model hubs.
AI and machine-learning integrations extend what an agent can do beyond its primary model — specialist models for embeddings, transcription, image work, or a second LLM used as a judge. Multi-model architectures are the norm in production: a cheap model for triage, a strong one for the hard step, an independent one for evaluation. Dezifi treats each as a credentialed, policy-scoped tool.
Integration
Anthropic
Anthropic integration for messages, models, token counting, and batch operations
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Integration
Azure OpenAI
Azure OpenAI integration for completions, chat, embeddings, deployments, models, images, transcription, and translation
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Integration
Hugging Face
Hugging Face integration for models, datasets, spaces, inference, repos, and user operations
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Integration
OpenAI
OpenAI integration for completions, chat, embeddings, models, images, files, fine-tuning, moderation, and assistants
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Integration
Vertex AI
Vertex AI integration for predictions, models, endpoints, datasets, training pipelines, batch predictions, and custom jobs
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What agents do with ai & machine learning tools
- Routing workflows that send easy cases to small models and hard ones up
- Transcription pipelines that turn calls into structured, searchable records
- LLM-as-judge evaluation of agent outputs against golden datasets
- Embedding generation for RAG datasets and semantic search