Ducky vs Nuclia
Detailed side-by-side comparison to help you choose the right tool
Ducky
🔴DeveloperAI Search & Embeddings
Ducky is fully managed AI search and RAG infrastructure — chunking, embedding, hybrid retrieval, and reranking behind a single API. The pitch is to skip the Pinecone + Cohere + LangChain glue and get a tuned retrieval pipeline in one HTTP call.
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CustomNuclia
🟢No CodeAI Search & Embeddings
Agentic RAG-as-a-service from Progress: auto-indexes PDFs, audio, video, and databases into a Knowledge Box and serves grounded, cited answers — EU-hosted and multilingual.
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CustomFeature Comparison
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Ducky - Pros & Cons
Pros
- ✓Compresses a multi-component RAG stack into one HTTP call
- ✓Hybrid retrieval + reranker is genuinely hard to operate yourself
- ✓Free tier is sufficient to ship a real prototype
Cons
- ✗Less control over chunking, embedding model, or reranker than rolling your own
- ✗Usage-based pricing scales with storage and queries — cost-modeling is fuzzy at high volume
- ✗No SaaS connector layer; you bring the documents yourself
Nuclia - Pros & Cons
Pros
- ✓Owns the full ingestion stack — no need to build OCR/transcription/chunking yourself
- ✓First-class multimodal and multilingual support is genuinely rare in managed RAG
- ✓MCP server makes it plug-and-play for agents built on Claude Desktop, Cursor, or Mastra
Cons
- ✗$700/mo Starter is expensive next to self-hosting open-source RAG on Vespa or Haystack
- ✗Starter tier is text-only and caps at 5GB indexed — multimodal use requires moving up tiers
- ✗Now folded into Progress's broader product portfolio, which may slow product iteration
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