{"id":5722,"date":"2026-10-26T17:49:35","date_gmt":"2026-10-26T06:49:35","guid":{"rendered":"https:\/\/exigotech.ethub.co\/services\/ai-and-automation\/build-your-ai\/rag-knowledge-assistants\/"},"modified":"2026-10-28T16:17:48","modified_gmt":"2026-10-28T05:17:48","slug":"rag-knowledge-assistants","status":"publish","type":"page","link":"https:\/\/exigotech.ethub.co\/au\/services\/ai-and-automation\/custom-ai-engineering\/rag-knowledge-assistants","title":{"rendered":"RAG & Knowledge Assistant Development | Exigo Tech"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":4704,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-5722","page","type-page","status-publish","hentry"],"acf":{"section_order":[{"section":"hero_banner_industry"},{"section":"services_about"},{"section":"core_offerings"},{"section":"our_experts"},{"section":"core_values"},{"section":"cta"},{"section":"partners"},{"section":"case_study"},{"section":"blogs"},{"section":"faqs"},{"section":"contact_us"}],"co_heading_bold":"Core Offerings:","co_heading_regular":"RAG & Knowledge Assistants Services","co_description":"We turn scattered organisational content into a tested knowledge assistant that gives users useful answers while keeping content ownership, permissions, and quality under control. ","co_offerings":[{"icon":3788,"title":"Use Case & Content Discovery","description":"We confirm who will ask questions, what they need to know and which sources hold the answers. We also flag outdated, duplicated or sensitive content that should be cleaned up or excluded first, and agree who owns each source.","image":5621,"link":""},{"icon":3788,"title":"Knowledge Base Design & Ingestion","description":"We set up Foundry IQ knowledge bases and Azure AI Search indexes over sources such as SharePoint, websites and document stores, with chunking, metadata and refresh schedules suited to your content. 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Retrieval-augmented generation (RAG) finds the most relevant passages in your documents, then a language model writes a reply based only on those passages and links to the source. This keeps answers specific to your organisation and far easier to check than a general chatbot."},{"question":"Should we use Microsoft 365 Copilot or Copilot Studio instead of a custom RAG assistant?","answer":"Often, yes. Microsoft 365 Copilot already answers from content in Microsoft 365, and Copilot Studio suits simpler assistants. A custom RAG assistant on Microsoft Foundry makes sense for customer-facing use, large or mixed content sources, strict quality targets or deep system integration. We recommend the simplest option that meets your needs."},{"question":"How do you stop the assistant making things up?","answer":"We ground every answer in retrieved content, instruct the model to say when it does not know, and show citations so users can check the source. Before launch, we test with real questions using Microsoft Foundry evaluators for retrieval quality, groundedness and relevance, then fix gaps in content or configuration before anyone relies on it."},{"question":"Will people see documents they should not?","answer":"Not when it is set up properly. We connect Microsoft Entra identity and carry document permissions into the search index, so results are trimmed to what each user can already access. We also exclude sensitive content that should not be indexed and align the design with your Microsoft Purview policies and labels."},{"question":"What content can a knowledge assistant use?","answer":"Common sources include SharePoint libraries, intranet and public web pages, PDFs and Office documents, Azure Blob Storage and structured data from business systems. During discovery, we check content quality and ownership, because an assistant is only as good as the material behind it. Outdated or conflicting documents are flagged for cleanup."},{"question":"What does a knowledge assistant cost to run?","answer":"Running costs come mainly from Azure AI Search capacity, usage of premium features such as agentic retrieval and semantic ranking, and model usage in Microsoft Foundry. We estimate these from your expected question volumes during design, set budgets and alerts in Azure, and tune the setup so costs stay predictable as usage grows."},{"question":"How do you keep answers accurate after go-live?","answer":"Content changes, so indexes refresh on a schedule and quality is rechecked with the same evaluation set used at launch. We hand over monitoring, a content ownership model and a simple process for flagging poor answers. If you would like us to run and improve the assistant for you, we can discuss ongoing support."},{"question":"Does Exigo Tech build knowledge assistants in Sydney, Melbourne, Adelaide and Wollongong?\u202f ","answer":"Yes. We design and build RAG knowledge assistants for organisations across Australia, including Sydney, Melbourne, Adelaide and Wollongong. Discovery workshops and user testing can run on-site or online, with local account management backed by our wider Microsoft AI engineering team.\u202f "},{"question":"Can our content and assistant stay in Australia?\u202f ","answer":"In most cases, yes. Microsoft Foundry and Azure AI Search are available in Australian Azure regions, and we confirm in-region availability for the models and features your design needs. We also review personal information handling with reference to the Privacy Act 1988. 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