Prometh

What is Prometh?

Prometh is a cognitive data framework designed to enhance the performance of AI models by improving data processing quality. It utilizes a semantic memory layer called Cognee to uncover hidden connections in data, making outputs more relevant and reliable. Prometh offers services such as data ingestion, data enrichment through knowledge graph mapping, and relevant data retrievals grounded in facts. Additionally, it aims to lower infrastructure costs by providing a robust and efficient big data infrastructure. Prometh has been praised for its effectiveness in various use-cases, such as improving accuracy and speed of retrievals for Keepi.ai and streamlining workflow and decision-making processes for dynamo.fyi.

Who created Prometh?

Prometh was created by Vasilije Markovic, who serves as the CEO & Co-Founder of the company. Vasilije has a background in Business, Psychology, and Engineering, with experience as a Team Lead at Taxfix, deploying machine learning applications at Zalando, and supervising the creation of real-time Big Data systems at Omio. The CTO & Co-Founder of Prometh is Boris Arzentar, who has an engineering and product growth background, having worked as a Growth Engineer at StuDocu, Frontend Lead at Pera, and Tech Lead at Knip/DIG.

What is Prometh used for?

• Offering save and retrieve knowledge capabilities to user base without needing fine-tuning or messing with vector databases
• Building a custom knowledge base of building codes and regulations for easy querying and updating
• Enriching data for thousands of customers and providing personalized support
• Building an affordable, reliable, and contextually aware memory layer for products

Who is Prometh for?

• Architect
• AI App Developers
• Data Analysts
• Engineers
• Data Enrichment Specialist

How to use Prometh?

To use Prometh effectively, follow these steps:

1. Data Ingestion: Start by uploading any kind of data, including unstructured text, media files, PDFs, tables, presentations, JSON files, and more. You can add small or large files individually or multiple files at once.

2. Data Enrichment: Prometh will extract facts and relationships from your data to create a knowledge graph. It establishes graph topology and connects related knowledge clusters, enabling Prometh to understand the data better.

3. Relevant Data Retrievals: The retrieval process is grounded in the gathered facts, reducing hallucinations in the output and ensuring reliable, relevant, and comprehensive results.

4. Lower Infrastructure Costs: Prometh provides a robust, efficient, and scalable big data infrastructure at a fraction of conventional storage expenses, saving you from the hassle of building it yourself.

5. Use-Cases: Prometh has been successfully used to offer knowledge capabilities, streamline workflows, provide personalized support to customers, and much more.

6. Testimonials: Users have praised Prometh for its ease of use, accuracy, speed of retrievals, and its ability to streamline decision-making processes and workflows.

By following these steps, you can effectively leverage Prometh to enhance your data management and retrieval processes, ensuring reliable and contextually aware outcomes.