Tired of incremental results with RAG?

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!
Tried and tested by the dev communities at:

Traditional RAG is a flawed framework

Traditional RAG is tedious and unreliable. consuming precious time and energy that you would rather spend building the application
Requires managing a Vector DB, chunking stategy & complex prompts
Retrieval is inaccurate and is based on similarity rather than logic or reason
The generation throws up probablistic responses and provides broader results
Deployment times could range anywhere from weeks to months, rasing prices.

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
iPhone mockup

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

Get inspired with our GitHub repository!

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.
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Built for Enterprise AI Developers

Now available on LangChain and LlamaIndex.

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.

For LlamaIndex

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.

The perfect tool for building GenAI applications

CogniSwitch Automates Gen AI Pipeline in 4 Steps


Whether it's documents, URLs or a cloud drive, seamlessly connect your sources of knowledge. Upload any form of unstructured knowledge


CogniSwitch uses the LLMs Natural Language prowess to help gather concepts, entities and their relationships from the knowledge provided


Unlike tradition RAG, CogniSwitch handles the storage of the mined concepts in a Knowledge Graph database, so that developers can focus on development


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
Reach out to us at: hello@cogniswitch.ai
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