What is RAG?
Retrieval Augmentation Generation (RAG) is mechanism for summarising your data without letting an LLM directly train on it. This then mitigating hallucinations, copyright concerns, minimises bias, enhancing explainability, and broadening cross-lingual reach.
What is GenAI?
Generative AI or GenAI for short is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data.
Generative AI and RAG Service Offerings
Many generative systems are training their systems on their users’ data, leading to PII, business/trade secrets, and even authentication details constituting part of the training. Our solution offering doesn’t train models on your data as we simply don’t need to.
Our solution removes the necessity of retraining models based on your data to accurately generate summaries and chatbot-style responses, because the very act of retrieval has already fine-tuned the data available to the generative model.
What we help you with
Some Large language models (LLMs) train their models on your data. Some hallucinate when they don’t know answers to your questions. Some lexical searches provide more relevant answers than solely semantic searches. RAG remedies all of this and our solution offers RAG-as-a-Service (RAGaaS) to enable you to build true business value with your data while keeping it safe and secure.
- Architecture and Implementation
- Development
- Business use cases
- Tactical implementation of security controls
- Compliance and Regulatory Guidance
- Data security and Privacy
Generative AI Security FAQ
Retrieval-Augmented Generation (RAG) is the process of optimising the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response.
AI is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.
Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data.
In simpler terms, machine learning enables computers to learn from data and make decisions or predictions without being explicitly programmed to do so. At its core, machine learning is all about creating and implementing algorithms that facilitate these decisions and predictions.
Natural language processing (NLP) is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language.
Benefits
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