Ducky

Ducky is a fully managed AI retrieval service. Easy to implement, blazingly fast, and incredibly accurate.

Freemium

Description

Ducky is a fully managed AI retrieval service engineered to streamline the complexities associated with semantic search and retrieval augmented generation (RAG). It empowers developers to effortlessly integrate advanced search capabilities into their applications, providing a solution that is characterized by its high speed and remarkable accuracy.

The platform adeptly manages various sophisticated aspects of AI-driven search, such as content chunking, query rewriting, hybrid search methodologies, and result reranking, all orchestrated within a comprehensive multi-stage system. By abstracting away the challenging underlying infrastructure concerns—including vector database selection, embedding model management, and operational scaling—Ducky enables builders to concentrate on creating context-aware AI agents and applications that deliver hallucination-free, well-informed, and highly relevant answers.

Key Features

Fully Managed Service: Simplifies retrieval augmented generation (RAG) by handling underlying complexities.
Great Performance: Engineered for high retrieval accuracy, low-latency search, and efficient indexing.
Fast Implementation: Offers a simple Python SDK and comprehensive documentation to start searching in seconds.
Fullstack Search Capabilities: Features a multi-stage system for chunking, query rewriting, hybrid search, and reranking.
Tool for AI Agents: Enhances LLM agents with context-awareness for generating informed, hallucination-free answers.
Simple and Clear Pricing: Includes a generous free tier with no credit card required to support builders.

Use Cases

Simplifying Retrieval Augmented Generation (RAG) for LLM applications.
Implementing advanced semantic search in websites and software applications.
Building context-aware AI agents with access to external knowledge bases.
Indexing and searching large volumes of documents or complex datasets efficiently.
Enhancing AI features by enabling accurate retrieval from custom data sources for tasks like quoting or deal analysis.

Frequently Asked Questions

What technical complexities does Ducky manage for AI retrieval?

Ducky handles several technical aspects of AI retrieval, such as selecting appropriate vector databases and embedding models, chunking large content, transforming user queries, implementing reranking, and managing the deployment and scaling of these systems, allowing developers to focus on building applications.

How quickly can developers integrate Ducky into their projects?

Developers can integrate Ducky and start performing searches within seconds using its simple Python SDK and comprehensive documentation, as Ducky manages all the backend infrastructure.

Is there a free plan available for Ducky?

Yes, Ducky provides a 'Build' tier which is free to use without requiring a credit card. This plan includes 100K index tokens and 100K retrieval tokens, suitable for hobbyists and small-volume projects.

How does Ducky help in building context-aware AI agents?

Ducky can be added to any LLM agent to provide context-awareness, enabling the agent to generate hallucination-free, informed, and relevant answers by retrieving pertinent information from indexed data.