Memory RAG

Features

Advanced RAG with a simple API interface

Our simple API interface enables developers to easily steer RAG applications to high accuracy with familiar development patterns.

Higher Accuracy RAG models

Contextual embeddings

Leverages embed-time compute during indexing to create higher-quality data representations for accurate and efficient retrieval.

95%

Accuracy with Memory RAG compared to 20% on GPT4

1 sec

Response time with Memory RAG compared to 2.7 seconds on GPT4

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Cost Efficient and Scalable

Smarter, more efficient RAG

Advanced RAG implementations are costly and complex. Memory RAG abstracts complexity and improves cost-efficiency.

Processing costs are incurred once during indexing rather than for every query

Query latency remains low even as data volume grows

Accuracy improves with more thorough initial processing

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Quality Control

Automated validation

Sophisticated checks verify information accuracy and consistency.

Automated content validation

Relationship verification

Consistency checking

Information completeness assessment

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How Memory RAG works

Embed-time compute—where the magic happens

Memory RAG leverages embed-time compute to process and enhance data during embedding creation, resulting in higher quality indexing and retrieval.

Automated knowledge distillation

Submit your documents, SQL schema, data, etc. via a prompt and the system will automatically specialize an LLM for you.

Enhanced processing

The specialized LMM identifies key information and relationships and creates contextual, validated embeddings.

Automated validation

Applies sophisticated checks to verify consistency and accuracy, forming the foundation for agent-based operations.

Intelligent compression

Automatically preserves the most important aspects of your information while removing redundancy

Optimized output

Data representations are optimized to enable fast and precise retrieval and efficient storage.

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Trusted by Fortune 500 and leading startups

100%

Accuracy for content classification

1200+h

Of manual work saved annually

"Lamini's classifier SDK is easy to use... Once [the tuned LLM] was ready, we tested it, and it was so easy to deploy to production. It allowed us to move really rapidly.”

Chris Lu

CTO

Introducing Memory RAG: build RAG agents with 90%+ accuracy

High-accuracy RAG without the complexity

Advanced RAG with a simple API interface

Contextual embeddings

Smarter, more efficient RAG

Automated validation

Embed-time compute—where the magic happens

Automated knowledge distillation

Enhanced processing

Automated validation

Intelligent compression

Optimized output

Trusted by Fortune 500 and leading startups

"Lamini's classifier SDK is easy to use... Once [the tuned LLM] was ready, we tested it, and it was so easy to deploy to production. It allowed us to move really rapidly.”