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Moreover, we don’t only write code but help you define the problem, pick the right ML approach, and turn your data into useful results.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-6265b283e7cb221380f9","name":"Can you deliver AI/ML services with a quick turnaround?","value":"“Yes, we can. Our team often works under tight deadlines.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-0014964bc88516cc49fc","name":"What are the key aspects of your AI/ML development services?","value":"“We focus on the following core areas: - Understanding your business needs - Working with quality data - Choosing the right models - Building clean and scalable code - Delivering real value Every project starts with not just building a model, but solving a real problem. We help you gather and prepare the right data, which is critical for success.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-eec880ac6bfc99d1126e","name":"Do you offer dedicated AI/ML developers on demand?","value":"“Yes, we offer dedicated AI/ML developers who can join your team as needed. This gives you flexibility without the cost and time of hiring full-time staff.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-6ac0904ddbc163934918","name":"How much does RAG development cost?","value":"“The cost of developing a RAG depends on the amount of data, the complexity of integrations, and security requirements. A prototype can cost $10k-30k; an MVP – $30k-120k; and a full enterprise RAG implementation with audits and production infrastructure usually starts at $120k and up.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-531a42e97bf588dcab15","name":"How long does it take to build an enterprise RAG chatbot?","value":"“A prototype can be implemented in 1-2 weeks, an MVP in 4-8 weeks. A full enterprise release, including security, integrations, and testing, usually takes 2-4 months.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-cf41d594c8d47fa759ad","name":"How do you implement retrieval-augmented generation (RAG)?","value":"“RAG is implemented through data auditing, construction of ingestion pipelines, proper document segmentation, vector search implementation, and retrieval and generation setup with access control. The key is to ensure accuracy, source citations, and secure integration with the company's infrastructure.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-27c70b5ff9e0acc1dc4b","name":"How to choose a vector database for RAG?","value":"“The choice of vector database depends on data scale, performance requirements, role filtering, and deployment model (cloud or on-premises). For the enterprise, metadata filter support, stability, and scalability are important.”"},{"@type":"PropertyValue","propertyID":"claim:content-native-digital-agencies-2857fb9ed1e742ec-a-5fda251adf06a0aef040","name":"What is the best RAG architecture for enterprise “chat over documents”?","value":"“The optimal RAG architecture implementation services include hybrid search, retrieval-level access control, source citation, and full system observability. It is important that RAG development services & solutions are managed, auditable, and meets security requirements.”"},{"@type":"PropertyValue","propertyID":"claim:source-description","name":"About","value":"Product-Driven Custom Software Development for Growing Businesses and Enterprises."},{"@type":"PropertyValue","propertyID":"claim:source-listed-website","name":"Website","value":"https://lumitech.co"}],"@type":"Organization"}}