Redefining
Retrieval-Augmented
Generation

PureCPP is a open-source RAG framework with superior Performance for Scalable Artificial Intelligence

Redefining
Retrieval-Augmented
Generation

PureCPP is a open-source RAG framework with superior Performance for Scalable Artificial Intelligence

Redefining Retrieval-Augmented Generation

PureCPP is a open-source RAG framework with superior Performance for Scalable Artificial Intelligence

Real-Time Data Recovery

The framework retrieves large volumes of structured and unstructured data instantly, delivering fast, accurate insights for critical decisions in sectors like legal and finance.

Scalable Integration

Built to scale, the framework adapts from small setups to large enterprises, maintaining high performance as data grows, ideal for expanding operations.

Data Vectorization

Extracted data is transformed into high-dimensional vectors using NLP, capturing the semantic meaning of text for precise understanding and retrieval.

Indexing with Metadata

Alongside vectorization, PureCPP indexes metadata like author, date, and topics, enriching search results and boosting traceability.

Capacity to Process +3,000 Files

PureCPP is designed to index over 3,000 files efficiently. Advanced vectorization and optimized indexing ensure it handles large data volumes without sacrificing speed or accuracy.

Real-Time Data Recovery

The framework retrieves large volumes of structured and unstructured data instantly, delivering fast, accurate insights for critical decisions in sectors like legal and finance.

Scalable Integration

Built to scale, the framework adapts from small setups to large enterprises, maintaining high performance as data grows, ideal for expanding operations.

Data Vectorization

Extracted data is transformed into high-dimensional vectors using NLP, capturing the semantic meaning of text for precise understanding and retrieval.

Indexing with Metadata

Alongside vectorization, PureCPP indexes metadata like author, date, and topics, enriching search results and boosting traceability.

Capacity to Process +3,000 Files

PureCPP is designed to index over 3,000 files efficiently. Advanced vectorization and optimized indexing ensure it handles large data volumes without sacrificing speed or accuracy.

How does PureCPP work?

Lightning-fast RAG with up to 66% better performance than conventional frameworks.

How does PureCPP work?

Lightning-fast RAG with up to 66% better performance than conventional frameworks.

Optimized for Developers, Loved by Machines

Lightweight and modular framework

Designed with speed and scalability in mind.

Best-in-class retrieval efficiency for AI pipelines.

PureCPP is ideal for projects that need an agile, scalable, and secure solution to process real-time data. It not only streamlines workflows but also ensures fast and accurate responses, improving decision-making and operational efficiency.

Optimized for Developers, Loved by Machines

Lightweight and modular framework

Designed with speed and scalability in mind.

Best-in-class retrieval efficiency for AI pipelines.

What is the difference between
our framework and the market today?

Comparison with samples of 3,000 PDFs

Comparison of CPU usage in identical processes

Up to 30% CPU usage savings

Estimated time for splitting text into chunks of 700 characters

66% speed increase

Estimated time for PDF extraction

60% speed increase

Access PureCPP on GitHub

What is the difference between our framework and the market today?