deepset Cloud Features

Here's what deepset Cloud enterprise ML/NLP platform offers

Custom NLP Pipelines

  • Question answering
  • Vector-based semantic search
  • Hybrid retrieval
  • Named entity recognition
  • Query classification
  • Pipeline templates

Prototypes & Feedback

  • Build shareable prototypes
  • Collect user feedback early
  • Analyze feedback qualitatively and quantitatively

Latest Models

  • Use deepset’s QA models with millions of downloads
  • Use GPT-3 models
  • Use Cohere Embedding models
  • Use any model from Hugging Face Hub
  • Upload private models

Scalable Cloud Document Store

  • Store 100M+ documents with meta data
  • Vector database
  • KNN search
  • Metadata filtering

Experiment Tracking

  • Quickly configure experiments
  • Run on auto-provisioned cloud infrastructure
  • Compare experiment runs
  • Traditional and model-based evaluation metrics
  • Easy access to predictions and qualitative error analysis
  • Tagging and adding notes

Deployment & Monitoring

  • 1-Click deployments on auto-scaling GPU or CPU infrastructure
  • Real-time updates on indexing status of your pipelines
  • Monitor requests, usage and latency

API & Integrations

  • Powerful REST API
  • Hugging Face integration


  • Data management via UI
  • Data management via API
  • Upload any pdf or docx file


  • Jupyter notebooks on GPU
  • Jupyter notebooks on CPU
  • SDK to connect directly to deepset Cloud from notebooks

Build NLP applications fast

From data to API-driven NLP backend services in days.