Chat with your own data, deployed at scale. Model agnostic with private embeddings.
Here's what we built
A private instance of a ChatGPT-like app that works on your own data.
Built-in workflows to embed large data lakes or data sources
Supports a wide range of data formats
Optimized semantic search to efficiently search through your data
All models stored and maintained privately
Works seamlessly with any private LLM
How can this be useful to you?
Three things: Insights, discoverability and unique content generation
Firstly, it can harness the power of semantic search and its deep understanding of language to unearth valuable insights from your own data. By understanding the user's intent and the contextual meaning of terms, it sifts through your data, drawing out connections and patterns that may not be immediately obvious. This allows you to make data-driven decisions with confidence, leveraging these insights to drive strategic planning and execution.
Secondly, private ChatGPT can significantly enhance discoverability within your organization. By deploying semantic search on top of your data, it can navigate through vast datasets to find the most relevant and accurate information in response to user queries. This can streamline internal processes, as team members can quickly find the information they need without wading through irrelevant data.
Lastly, private ChatGPT can serve as an invaluable tool for unique content generation based on your past content. Given a seed of information or a set of guidelines, it can generate creative and engaging content, from technical reports to marketing copy. This not only saves time and resources but also ensures consistency and quality in your organization's communications. Thus, a private ChatGPT instance can serve as a powerful ally, transforming the way your organization handles data, discovers information, and creates content.
Our tooling gives us a head start
We built our capabilities to deliver this solution by first building an open-source version of a private Chatgpt that works with OpenAI's endpoints. This helped us understand the nuances of bringing a solution like this into an organization's private environment.
Also, Paradigm has been developing its own MLOps tool which is open-source.
This experience and expertise we have gained by building scalable AI solutions on top of Kubernetes sit at the foundation of Private ChatGPT.