Pongo : Pongo, a semantic filter, can reduce LLM hallucinations in RAG workflows by up to 80% with a single line of code.

Development & Tools

Pongo

Pongo

Pongo

Development & Tools AI Model #Semantic Filter #RAG Workflow #Semantic Similarity #Information Retrieval Standard Picks Paid

Overview :

Pongo's semantic filter leverages a line of code to decrease LLM hallucinations in RAG workflows by as much as 80%. It utilizes advanced semantic similarity models and proprietary ranking algorithms to ensure you always receive accurate information. Pongo integrates seamlessly with existing workflows, offering fast response times and zero data retention.

Target Users :

Pongo is designed for RAG workflows where reducing LLM hallucinations is critical. It empowers users to quickly and accurately retrieve relevant information.

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Use Cases

Improve the accuracy and relevance of search engines

Optimize text classification and recommendation systems

Enhance the quality of answers in question-answering systems

Features

Reduces the occurrence of LLM hallucinations in RAG workflows

Provides semantic similarity search

Supports existing workflows

Distributed architecture for fast response

Zero data retention

How to Use

Add Pongo's semantic filter module to your code

Send the text you need to process to Pongo

Receive the filtered results

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