Audience
Companies wanting a solution to search, quantify and edit data for LLMs
About Lilac
Lilac is an open source tool that enables data and AI practitioners to improve their products by improving their data. Understand your data with powerful search and filtering. Collaborate with your team on a single, centralized dataset. Apply best practices for data curation, like removing duplicates and PII to reduce dataset size and lower training cost and time. See how your pipeline impacts your data using our diff viewer. Clustering is a technique that automatically assigns categories to each document by analyzing the text content and putting similar documents in the same category. This reveals the overarching structure of your dataset. Lilac uses state-of-the-art algorithms and LLMs to cluster the dataset and assign informative, descriptive titles. Before we do advanced searching, like concept or semantic search, we can immediately use keyword search by typing a keyword in the search box.
Pricing
Starting Price:
Free
Free Version:
Free Version available.
Company Information
Lilac
United States
www.lilacml.com
Videos and Screen Captures
Azure Open Datasets
Improve the accuracy of your machine learning models with publicly available datasets. Save time on data discovery and preparation by using curated datasets that are ready to use in machine learning workflows and easy to access from Azure services. Account for real-world factors that can impact business outcomes. By incorporating features from curated datasets into your machine learning models, improve the accuracy of predictions and reduce data preparation time. Share datasets with a growing community of data scientists and developers. Deliver insights at hyperscale using Azure Open Datasets with Azure’s machine learning and data analytics solutions. There's no additional charge for using most Open Datasets. Pay only for Azure services consumed while using Open Datasets, such as virtual machine instances, storage, networking resources, and machine learning. Curated open data made easily accessible on Azure.
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Ragie
Ragie streamlines data ingestion, chunking, and multimodal indexing of structured and unstructured data. Connect directly to your own data sources, ensuring your data pipeline is always up-to-date. Built-in advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search help you deliver state-of-the-art generative AI. Connect directly to popular data sources like Google Drive, Notion, Confluence, and more. Automatic syncing keeps your data up-to-date, ensuring your application delivers accurate and reliable information. With Ragie connectors, getting your data into your AI application has never been simpler. With just a few clicks, you can access your data where it already lives. Automatic syncing keeps your data up-to-date ensuring your application delivers accurate and reliable information. The first step in a RAG pipeline is to ingest the relevant data. Use Ragie’s simple APIs to upload files directly.
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Pinecone
Long-term memory for AI.
The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval.
Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results.
Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.
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Pigro
ChatGPT retrieval plugin on steroids. Intelligent document indexing services for smarter answers. In order to get accurate ChatGPT answers it's crucial to have spans of text that respect the context of the original document. Current OpenAI text chunking services split the text based only on punctuation marks every 200 words. Pigro provides AI-based text chunking services that split content like a human would, considering the look and structure of the document, such as pagination, headings, tables, lists, images, etc. Our API natively supports Office-like documents, PDF, HTML, and plain text in many languages. Pigro delivers only the most relevant spans of text that answer the query. Our generative AI expands each of your content: we generate all possible questions answered within your document. Our search uses keywords and semantics, considering the title, body, and generated questions. Best-in-class accuracy with generative indexing.
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Product Details
Platforms Supported
Linux
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