Needle 2.0
AIKnowledge-threading platform for fast AI-powered information discovery, automation, and RAG APIs across your data sources.
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Paid
See pricing details
Needle 2.0
AI
Knowledge-threading platform for fast AI-powered information discovery, automation, and RAG APIs across your data sources.
-(0 Reviews)
Paid
See pricing details
About Needle 2.0
Needle is a knowledge-threading platform that enables fast, AI-powered information discovery and automation across multiple data sources. It provides a Retrieval-Augmented Generation (RAG) API and managed RAG pipelines so developers can build agentic AI applications and long-term memory for LLMs. Needle offers developer tooling (including a Python SDK) to extract key points and contextual threads from files, integrate with third-party LLM providers, and orchestrate production-ready retrieval and memory workflows.
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Key Features
Knowledge Threading Search: Extracts key points and threads of knowledge from documents and files to enable fast, context-rich information discovery across disparate data sources.
RAG API for Agentic Apps: Exposes a Retrieval-Augmented Generation API that developers can use to build agentic AI applications by combining Needle retrieval with any LLM provider for generation.
Managed RAG Pipelines and MCP Server: Provides production-ready managed RAG pipelines and an MCP server offering long-term memory orchestration for LLMs, reducing operational overhead for retrieval and memory management.
Python SDK (needle-python): Offers a first-class Python client that reads API keys from environment, simplifies calling the Needle API, and includes tutorials and examples to compose RAG pipelines (e.g., with OpenAI).
Multi-Source Integration: Connects to and indexes content across all your data sources to provide unified search, automated context extraction, and retrieval for downstream LLM prompts.
Automated Context Extraction: Instantly extracts salient points and structured context from files to reduce prompt engineering and improve LLM answer quality.
RAG REST API for retrieval-augmented generation and agentic applications
Python SDK (needle-python) that reads NEEDLE_API_KEY from environment and simplifies RAG workflows
MCP server repository for long-term memory / memory control plane
Managed RAG pipeline examples and production-ready TypeScript components
Docker-based unified installation and service orchestration (backend, generator hub, infra)
needlectl CLI to manage services and lifecycle
Context extraction from files (instantly extracts key points)
Integration examples with LLM providers (OpenAI example included in docs)
Use Cases
Building agentic AI applications that use Needle's RAG API to retrieve relevant context and combine it with LLMs for decision-making and task automation.
Implementing RAG-based QA over company knowledge bases and document stores by extracting key points and feeding them into an LLM for accurate, context-aware answers.
Providing long-term memory for conversational agents by using Needle's MCP/managed pipelines to store, retrieve, and update persistent context across sessions.
Automating information discovery and internal workflows by connecting Needle to multiple data sources and triggering automated actions or synthesized summaries.
Developer integration and prototyping: Using the needle-python SDK to rapidly prototype retrieval + LLM pipelines (e.g., Needle for retrieval + OpenAI for generation) with simple API-key-based setup.
Build RAG-based assistants that combine document stores and LLMs
Create agentic applications that need retrieval + long-term memory
Implement production-managed RAG pipelines and orchestration
Embed contextual search and information discovery across multiple data sources
Prototype or deploy image-retrieval or other research-backed retrieval systems using provided Docker stacks