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AI Knowledge Base Development
AI knowledge base development gives staff or customers one place to ask questions and get answers grounded in your own documents. Shyphan builds retrieval-augmented generation (RAG) systems over policies, manuals, contracts and wikis that cite the passage they used, respect existing access rights and say plainly when the answer is not in the source material.
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The first AI Enabled Zoho Partner in the Middle East and Africa. Accredited by Zoho on 14 October 2026 after the Zoho AI Accelerator Series. Read the announcement
AI Enabled Zoho Partner in 21 countriesTrusted by businesses across the UAE, Saudi Arabia and beyond
AI Knowledge Base Development: the short answer
- What it is
- An AI knowledge base indexes company documents in a vector database and uses a language model to answer questions only from the passages it retrieves.
- Best suited to
- Organisations with large, scattered document collections, such as policy libraries, technical manuals or SOPs, where staff waste time searching or ask colleagues the same questions.
- Core stack
- pgvector, Qdrant, LlamaIndex, Anthropic Claude, Azure OpenAI, SharePoint
- Typical timeline
- A four to six week pilot on one workflow, measured against agreed success criteria, then a phased rollout.
- What it costs
- A fixed quote for the pilot after a free discovery call; model and hosting usage costs are shown separately.
- Across markets
- Personal data in documents; In-region vector storage; Ask in Arabic, find English.
- Delivered by
- Shyphan AI Solutions: AI, Zoho, Odoo, Dynamics 365 and custom software under one team, with remote delivery worldwide.
- Last reviewed
- 30 September 2026
AI Knowledge Base Development: who it is for
Organisations with large, scattered document collections, such as policy libraries, technical manuals or SOPs, where staff waste time searching or ask colleagues the same questions. An AI knowledge base indexes company documents in a vector database and uses a language model to answer questions only from the passages it retrieves.
- Answers with citations
- Permission-aware retrieval
- Automatic content sync
- Chunking and retrieval tuning
What we use to deliver AI Knowledge Base Development
The tools we typically use. The final choice is made against your systems, budget and team.
AI Knowledge Base Development: what is included
AI knowledge base development gives staff or customers one place to ask questions and get answers grounded in your own documents.
Answers with citations
Every answer links to the document and passage it came from, so readers can check it in seconds. If retrieval finds nothing relevant, the assistant says so rather than guessing from general knowledge.
Permission-aware retrieval
The index carries access rights from SharePoint, Google Drive, WorkDrive or your file store. A user only gets answers from documents they are already allowed to open, which keeps HR and finance content private.
Automatic content sync
Connectors keep the index current as documents are added, edited or retired in their source systems. Outdated versions are removed automatically, so the assistant does not quote a policy that was replaced last quarter.
Chunking and retrieval tuning
We split documents by headings and tables, not arbitrary lengths, combine keyword and semantic search and re-rank results. This tuning is where most answer quality comes from, and we measure it separately.
Answer quality evaluation
A test set of real questions with known correct answers is scored for accuracy, citation correctness and refusal when the answer is missing. Scores are rerun after every content, prompt or model change.
Where people ask
The assistant can live in Microsoft Teams, Slack, your intranet, a helpdesk agent screen or a customer portal. One index serves several front ends, each with its own access rules and tone.
The systems it plugs into
Real screens from the platforms we work with. Yours are configured to your entities, processes and KPIs.
Executive KPI dashboard in Zoho Analytics
Leads, conversions, revenue, expenses, profit, tickets and satisfaction on one board, drawn from Zoho CRM, Expense and Desk. Your AI assistant reads from and writes back to screens like this one, so nothing is re-keyed.
- Answers with citations
- Permission-aware retrieval
- Automatic content sync
Sales dashboard in Odoo
Quotations, orders, revenue and average order value with the monthly trend, built from live Odoo data. The same AI assistant connects to Odoo in exactly the same way.
- Chunking and retrieval tuning
- Personal data in documents
- In-region vector storage
How AI Knowledge Base Development changes by market
Tax, e-invoicing, data protection and language rules differ by country. We confirm the current position for each market at scoping.
Personal data in documents
HR files and contracts often hold personal data, so GDPR, UK GDPR, India DPDP, UAE PDPL and Saudi PDPL apply to the index as well as the originals. We exclude or restrict such content. We confirm the current rules at scoping.
In-region vector storage
Embeddings and indexes can be stored on your own cloud in a chosen region, with models on regional Azure OpenAI or self-hosted open models, so documents never leave the required jurisdiction.
Ask in Arabic, find English
Staff can ask in Arabic and get answers from English documents, or the reverse, with the citation in the original language. We use multilingual embeddings and test cross-language retrieval.
How we deliver AI Knowledge Base Development
Phases, indicative timing and what is delivered in each. Scope is fixed and quoted before we start.
Content inventory
List document sources, owners, access rules and formats, and remove duplicates and obsolete versions before indexing.
Question set
Collect real questions from staff, with agreed correct answers, to act as the evaluation benchmark throughout.
Index and retrieval
Build connectors, chunking, embeddings and hybrid search, then tune retrieval quality against the question set.
Assistant and interface
Add the answer layer with citations and refusal rules, and connect the chosen chat interface for users.
Pilot and upkeep
Pilot with one department, track unanswered questions and fix the content gaps with the document owners.
When AI Knowledge Base Development is the wrong answer
A knowledge base is only as good as the documents behind it. If policies contradict each other or live in people's heads, the assistant will reflect that. We will suggest a content clean-up first. If you need data pulled into systems rather than answers, document processing is the right service.
How we handle it: We implement Zoho, Odoo and Dynamics 365 and build AI and custom software, so our written recommendation can point you to a simpler option, or to doing nothing yet.
One team, seven offices, delivery worldwide
We deliver AI projects from our headquarters in Noida, India, and offices in Ras Al Khaimah, Riyadh, Beirut, Istanbul, Lagos and London, with remote delivery worldwide and on-site workshops when a project needs them. Pictured: our team at Zoholics Dubai 2026.
AI Knowledge Base Development: questions we get asked
What is AI knowledge base development with RAG?
How is a knowledge base different from an AI chatbot?
Can it respect who is allowed to see what?
Do you train a model on our documents?
Which vector database do you use?
How long does it take to build?
Why choose Shyphan?
Talk to a consultant about AI Knowledge Base Development
A free 30-minute call, then a written recommendation and a fixed quote, including the honest option that this is not the right fit.
