No credit card required - we have a generous free tier to support builders
Which vector database
What is a good embedding model
How to chuck large content
How to transform user queries
How to implement reranking
How to deploy these systems
How to scale with volume
All retrieval in one place
Seamless integration
Simple, clear pricing
Fully managed
Great performance
Built for retrieval accuracy, low-latency search, and efficient indexing — delivering relevant results, not just similar ones.
Get going fast
Built for developers - A simple Python SDK with comprehensive docs. Start searching in seconds, while Ducky handles the infra.
Fullstack search
Our multi-stage system handles complex search intent with chunking, query rewriting, hybrid search, reranking, and more.
Tool for agents
Add Ducky to any LLM agent for a context-aware agent. Generate hallucination-free, informed, and relevant answers.
from duckyai import DuckyAI
ducky = DuckyAI(api_key="your-api-key")
ducky.indexes.create(index_name='my-documents')
ducky.documents.index(index_name='my-documents', content='Hello, World!')
results = ducky.documents.retrieve(
index_name='my-documents',
query='hello',
top_k=1,
)
Build
For hobbyists looking to explore
Free
no credit card required
100K index tokens
100K retrieval tokens
Grow
For apps released into the wild
$480
$290
per month
1M index tokens each month
1M retrieval tokens each month
$0.014 per additional 1K index tokens
$0.079 per additional 1K retrieval tokens
Support via Slack
Enterprise
Get in touch to discuss higher volumes
No credit card required - we have a generous free tier to support builders
Ducky simplifies retrieval. It’s that straightforward. Setup takes 5 minutes, and everything functions seamlessly. No need to worry about embeddings, chunking, re-ranking, or other complexities. Ducky handles it all. Just upload your data and get back to building.
Rich Scudellari, Penny Jar
We love Ducky for its speed and accuracy. It bypasses token limits by auto-indexing long files into searchable chunks, streamlining our workflow and boosting results.
Jeff Brunelle, HDBND
Ducky made indexing our quoting and deal data for Vendori’s AI features effortless. Despite our complex use case, it delivered flawless retrieval and generation.
Ethan Garonzik, Vendori
Ducky has been a game-changer for our RAG workflows. Within hours, we had a fully functional, low-latency semantic search pipeline without the overhead of managing embeddings, vector databases, or rerankers.
Rick Voltz, Oversite