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Sycamore:
An LLM-powered, conversational search and analytics platform.

Use Sycamore to answer questions on your complex unstructured data. Customize RAG pipelines, and go beyond RAG with analytics.

AI-powered segmentation, enrichment, and structuring tools to prepare your data for high-quality results.

 

Built on OpenSearch for scalable vector indexing and enterprise-grade security.

High-quality answers

Secure and scalable

100% open source, Apache v2.0

To get the right answers, simple RAG is not enough. When data gets complicated, developers reach for Sycamore.

Product

One-stop Shop for Developers

Everything you need to build conversational apps on complex unstructured data, from data crawling to preparation to indexing to conversational APIs. Iterate and get to production faster, and scale up seamlessly as your dataset grows.

LLM-powered
Data Enrichment

Robust and scalable API to construct Python-native data pipelines to clean, segment, enrich, and structure complex data in PDFs, HTML, tables, and graphics. Leverage LLMs to extract and manipulate data, and generate vector embeddings.

High-quality Search and Analytics

Higher-quality answers with APIs for conversational RAG, hybrid search (vector and keyword), and analytics on structured metadata (OpenSearch API compatible). You can also use post-processors like re-ranking and near-duplicate detection.

Open Source and Customizable

100% open source (Apache License v2.0), with the freedom to customize and build. Built with OpenSearch, an enterprise grade search engine. Easily experiment with different generative AI models and customize search pipelines.

Sycamore architecture diagram

Versatile to handle the complexities of
your data.

Deploy Sycamore with Docker and choose your hardware. Use default data preparation code or pipelines that are customizable with a built-in Jupyter notebook. Choose your LLMs and data processing AI models, ingest your data, and query it with natural language or analytics. Sycamore uses a scalable, secure, and customizable OpenSearch backend for indexing and data retrieval.

End-to-end stack

LLM-integrations

Scale up quickly

Sycamore demo videos:

See how you can harness your unstructured data with Sycamore.

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Use cases.

Developers use Sycamore as a core building block for search and analytics applications in financial services, healthcare, manufacturing, eCommerce, and customer support. 

Research and discovery

Build apps to enable analysts and researchers to ask hard questions on complex unstructured data that includes tables, infographics, and complicated layouts. Discover and use critical information that would otherwise be missed.

Reporting on unstructured data feeds

Create structured reports from unstructured data to answer key business questions. Run scheduled pipelines that extract, enrich, and store information from diverse datasets, such as Salesforce data, health records, or contracts.

Technical knowledge bases

Empower technical knowledge workers with AI-assistants for manuals, technical documents, installation guides, and catalogs to quickly answer technical questions and find information. Get direct answers and pointers to sources.

Customer support

Create co-pilots to empower customer support teams, healthcare professionals, or empower customers to directly query knowledge bases, support tickets, FAQs, healthcare records, and other information sources. 

Meet Aryn.

Aryn (pronounced "air-in") means "high mountain." Over 90% of data today is unstructured, leaving enterprises with mountains of data that are difficult to conquer. Our goal is to help you summit that peak.

Leadership Team.

Aryn's team includes leaders with decades of big data, AI, and cloud experience from AWS, Google Cloud, Stripe, Dremio, HP, IBM, Yahoo!, and Meta.

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Investors.

Aryn has a $7.5M seed investment from Factory HQ, 8VC,
Lip-Bu Tan, Amarjit Gill, and other notable angels and advisors. Read 8VC's investment announcement.

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