Provides an AI memory engine that integrates with existing language model (LLM) infrastructure to improve data understanding and response accuracy. By mapping knowledge graphs and identifying hidden data connections, it enables LLM applications to deliver more relevant outputs for tasks like text generation, customer analysis, and chatbot interactions.
Funding
$1.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
4CAICVFounders
Product
Problem
Large language models (LLMs) often struggle with accuracy because they lack a deep understanding of the data they process, leading to unreliable outputs. LLMs understand how words relate to each other, but not what they actually mean.
Solution
Cognee provides an AI memory engine that integrates with existing LLM infrastructure to improve data understanding and response accuracy. The engine uses machine learning techniques to mimic human data processing by consolidating information into 'memories'. By mapping knowledge graphs and identifying hidden data connections, Cognee enables LLM applications to deliver more relevant outputs. This leads to more reliable responses from LLM applications in areas like text generation, content summarization, customer analysis, chatbot responses, code generation, and translations.
Target Audience
Primary customers are developers and businesses using LLMs who need to improve the accuracy and reliability of their AI applications.
Features
- Connects data points to uncover previously hidden links.
- Improves the quality and reliability of LLM outputs.
- Handles increasing amounts of data and user demands without performance loss.
- Integrates with over 28 standard ingestion sources.
- Provides a data store, reducing the need for expensive OpenAI APIs.
- Deploys on customer systems for full data control and regulatory compliance.
- Offers custom schema and ontology generation.
- Includes integrated evaluations.