GenAI developers are running into the same problems with the traditional RAG framework. Reliability, storage, retrieval and to top it off high failure rates.
RAG was a step in the right direction but CogniSwitch is the solution!
CogniSwitch with its Knowledge Graph RAG approach automates the grunt work for you
Unlike Traditional RAG, CogniSwitch's approach is helping developers automate the entire production pipeline, cutting deployment times to less than 3 days!
Connect & Ingest
CogniSwitch's APIs allow you to connect your sources of knowlwedge, wherever or whatever form they maybe in
Storage decisions handled
Unlike tarditional RAG, CogniSwitch handles decsions related to storage, plotting the knowledge graph with information
Enhanced Retrieval
Unlike traditional RAG that involves a similarity based search, CogniSiwtch is deterministic thanks to the Knowledge Graph
100% Accuracy w/ Proof
CogniSwitch ensures the responses generate are grounded in facts acting as guardrails and back it up with provenance for testing
Need a little help getting acquainted with CogniSwitch? Not to worry, just browse through our GitHub repository that contains details on how to use CogniSwitch. It also contains instructions to help use it along with popular frameworks like LangChain and LlamaIndex.
Worried about having to master a new tool? Don’t be! If you know how to make an API call, that's all you need to use CogniSwitch and bring better functionality to your applications.
With API documentation to walk you through the setup CogniSwitch is a worthy addition to a developer's arsenal 1. Click on the button below! 2. Signup on the platform to get your API tokens 3. Get Started on your next project
Use our APIs to seamlessly connect with your favorite tools. Plugin to sources where your data resides to ingest your resident knowledge.
For LangChain
CogniSwitch Toolkit on LangChain relieves developers from the stress of choosing the right storage and retrieval formats. Get started by interacting with your knowledge in just two simple steps.
CogniSwitch's Graph RAG solves for both ingestion and retrieval. Use this to store data from File or URL. Query in natural language and get a natural language answer using CogniSwitch Tool spec.
Whether it's documents, URLs or a cloud drive, seamlessly connect your sources of knowledge. Upload any form of unstructured knowledge
Curate:
CogniSwitch uses the LLMs Natural Language prowess to help gather concepts, entities and their relationships from the knowledge provided
Stroage:
Unlike tradition RAG, CogniSwitch handles the storage of the mined concepts in a Knowledge Graph database, so that developers can focus on development
Provision:
Just like that you’re ready to query your knowledge from any tool of your choice. Provide the knowledge your teams or customers need where it’s most convenient for them