AI Data Pipeline (Beta)
Securely connect your digital workplace data to Large Language Models (LLMs) via Retrieval-Augmented Generation (RAG).
Your enterprise data + LLMs
Using generative AI with your enterprise data unlocks powerful possibilities for your organization. Successful generative AI adoption starts with a strong data foundation. With Onna, you can build a centralized repository for unstructured data from your digital workplace tools, and create a secure pipeline that connects your data to LLMs.
Contact us to learn moreHow to create an AI Data Pipeline with Onna
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1. Centralize
Centralize unstructured data from your digital workplace
Use no-code connectors for common collaboration, communication, and chat tools to centralize the data you want to use with LLMs.
Don't see a connector for one of your data sources? Learn more about how to use our Platform API to ingest data from custom sources.
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2. Curate
Curate an LLM-ready dataset
Prepare data for use with LLMs by creating highly curated datasets. Use source-specific parameters to ingest exactly what you need. Visibility into the data allows you to identify what you want to use and filter out what you don't.
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3. Transform
Automatically transform data into a useable format and calculate vector embeddings
Onna's processing pipeline transforms and standardizes unstructured data into a useable asset. In addition to processing and indexing multiple file types, Onna will calculate and store vector embeddings to power a Retrieval-Augmented Generation (RAG) workflow.
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4. Manage
Strategically organize and manage data in Onna
Organize data into Workspaces so you can further audit and examine data used with LLMs. Search, tag, and classify your data, and securely invite team members to each Workspace to collaborate on your data management initiatives.
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5. Connect
Select & connect to your preferred LLM
Onna's platform is LLM agnostic, so you can leverage your preferred LLM. Use API keys to connect your curated dataset to the LLM you want to use.
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6. Activate
Empower users across your business with generative AI, built on your data
With your enterprise data centralized, curated, and LLM-ready, you can create business-specific generative AI applications. Whether it's a chatbot for the marketing team, or a contract analysis tool for the legal team, or something else, you can use Onna to leverage LLMs with your data.
Reach out to Onna's team to learn more about how we can support your generative AI initiatives.
Contact us to learn more
Centralize unstructured data from your digital workplace
Use no-code connectors for common collaboration, communication, and chat tools to centralize the data you want to use with LLMs.
Don't see a connector for one of your data sources? Learn more about how to use our Platform API to ingest data from custom sources.
Curate an LLM-ready dataset
Prepare data for use with LLMs by creating highly curated datasets. Use source-specific parameters to ingest exactly what you need. Visibility into the data allows you to identify what you want to use and filter out what you don't.
Automatically transform data into a useable format and calculate vector embeddings
Onna's processing pipeline transforms and standardizes unstructured data into a useable asset. In addition to processing and indexing multiple file types, Onna will calculate and store vector embeddings to power a Retrieval-Augmented Generation (RAG) workflow.
Strategically organize and manage data in Onna
Organize data into Workspaces so you can further audit and examine data used with LLMs. Search, tag, and classify your data, and securely invite team members to each Workspace to collaborate on your data management initiatives.
Select & connect to your preferred LLM
Onna's platform is LLM agnostic, so you can leverage your preferred LLM. Use API keys to connect your curated dataset to the LLM you want to use.
Empower users across your business with generative AI, built on your data
With your enterprise data centralized, curated, and LLM-ready, you can create business-specific generative AI applications. Whether it's a chatbot for the marketing team, or a contract analysis tool for the legal team, or something else, you can use Onna to leverage LLMs with your data.
Reach out to Onna's team to learn more about how we can support your generative AI initiatives.
Contact us to learn more
Retrieval-Augmented Generation (RAG) with Onna
RAG is a technique for optimizing LLM predictions and reducing hallucinations. It enables LLMs to reference information from domain-specific datasets to inform responses. No model retraining is required, which makes RAG a cost-effective method for developing specialized AI applications.
"Because no retraining is involved and everything is done via in-context learning, RAG-based inference is fast (sub 100ms latency), and well-suited to be used inside real time applications."
RAG vs Fine-tuning LLMs-What to use, when, and why. | John Hwang, Substack
RAG vs Fine-tuning LLMs-What to use, when, and why. | John Hwang, Substack
Learn more about RAG, GenAI use cases, and Onna's AI principles
Check out these resources to learn more about RAG and Onna's approach to AI.
Blog
What is Retrieval-Augmented Generation (and why should every legal professional know about it)?
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Join the AI Data Pipeline Beta
Ready to get started? Reach out to learn more about joining the beta program or with any questions.
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