Enterprise Grade Document ETL for Production Ready GenAI Data

Scalable Document Pipelines

Effortlessly scale to ingesting and managing millions of documents across many enterprise systems. Automation that keeps data fresh

Composable Design

Built-in modules for parsing, chunking, and embedding with flexibility to bring any best-in-class component of your choice.

Metadata Enabled

Automated metadata management enables citations, rich context, and lineage, all out of the box in our enterprise-grade solution

Converged Integration

GenAI Ready Data that includes information from Databases, APIs, and real-time feeds to supplement Document based data.

NVIDIA Accelerated

Our partnership with NVIDIA brings NIMs that accelerate parsing and embedding generation during ETL

Get Your Data GenAI Ready with Enterprise-Grade Features

Document Connectors
VectorDB Integration
Parsing Orchestration
Advanced Chunking
Flexible Embeddings
Metadata + Embeddings
File Management
Easy Experiementation

Rich connectors for any and all document stores across Sharepoint, SFTP, S3, Dropbox, Box, Google Drive and more to make enterprise wide documents GenAI ready.

Built-in integrations enable  no-code pipelines for embeddings to the vector database of your choice  including Pinecone, Weaviate, and MongoDB with new connectors delivered under 24 hours

We deliver best in class solution by orchestrating between our built-in PDF parser and advanced parsers from external providers including AWS Textract, Tesseract OCR, and Unstructured

Enhanced chunking algorithms from Nexla improve context retention, but give you the freedom to build or bring your own chunking code in Python.

Multiple choices for Embeddings including OpenAI, Cohere, NIMs, Voyage, and more. It takes minutes to add a new algorithm

Enhance your final outcomes with metadata infused embedding generation for powerful citations and data freshness management

Manage millions of files easily as Nexla track previously ingested files with easy interface to re-ingest, detect new files, changed files, and discard old data

Apply multiple methodologies simultaneously to compare results or try new techniques without disrupting existing solutions

Use Cases Powered by Document ETL

Analyze Legal and Financial Filings, Documents

Financial and Legal filings add up to vast volumes of public and non-public data. Converting this data to embeddings makes it GenAI Ready for a RAG model to leverage this data for query, summarization, and answer generation.

Insights from User Generated Content

Public product reviews, social media content, survey information, and other user generated information is now with reach for analysis as text or upon conversion to structured data

Summarize Notes in Enterprise Apps EHR/EMR CRM ERP

Valuable notes across your EHR/EMR systems in Healthcare, CRMs in Sales, ERP Tools and many more such systems can immediately be ready for use with LLMs, connecting insights from across systems into coherent answers and analysis