Custom LLM Solutions
We focus on using the Retrieval Augmented Generation (RAG) methodology on Large Language Models (LLMs) to create customised AI solutions for your company. These solutions ensure your private and confidential content such as company databases, files, policies and customer data remains within your own servers and systems, instead of going to cloud-based LLMs, which may be used for external training.
Retrieval Augmented Generation
Retrieval-Augmented Generation (RAG) for LLMs enhances AI responses by retrieving relevant external data before generating answers. Instead of relying solely on pre-trained knowledge, RAG dynamically pulls real-time, domain-specific, or proprietary information to improve accuracy and relevance.
Companies should use RAG to keep AI responses up-to-date, reduce hallucinations, and integrate proprietary knowledge without retraining models. This boosts efficiency, personalization, and trust in AI-driven applications, making it ideal for customer support, research, and enterprise solutions. By combining retrieval with generation, businesses can ensure their AI remains informed, adaptable, and cost-effective.
Customized RAGs
RAG can be implemented in various ways to handle different data sources. For PDFs, it extracts and indexes text for retrieval. For databases, it queries structured data dynamically. For websites, it scrapes and fetches live content. Each company needs a unique RAG setup tailored to its data sources, security policies, and business needs.
Customization ensures AI retrieves the most relevant and accurate information, enhancing decision-making, customer interactions, and operational efficiency. A one-size-fits-all approach won’t work—companies must design RAG to integrate seamlessly with their proprietary knowledge, ensuring competitive advantage and reliable AI-driven insights.
Affordable, Powerful, and Easy
RAG is a fast, cost-effective, and easy-to-implement solution for enhancing AI capabilities. Unlike expensive model retraining, RAG integrates with existing data sources—PDFs, databases, websites—without major infrastructure changes. It improves accuracy instantly by fetching real-time, relevant information while keeping costs low.
Deployment is quick, requiring only lightweight indexing and retrieval mechanisms, making it ideal for businesses of any size. With minimal setup and immediate benefits, RAG offers a scalable, efficient way to supercharge AI applications. If you want smarter, more reliable AI without breaking the bank, RAG is the perfect solution for your business.
