Your policies, contracts, manuals and procedures already hold the answers. Data Semantics builds knowledge assistants that answer in plain language, cite the exact source and respect who may see what, tested for accuracy before anyone relies on them.
Your knowledge
SharePoint & file sharesPolicies & contractsManuals & proceduresScanned documentsERP & CRM recordsWe build
Your permissions respected
Where people ask
Microsoft TeamsCopilotYour intranet & appsData Semantics builds enterprise knowledge assistants on Azure AI Search, Azure OpenAI, Claude or open-weight models, and Copilot Studio, connected to SharePoint, file shares, line-of-business systems and your data platform. They respect existing permissions, use your ontology to understand business terms, and are tested against real questions before go-live.
Policies, contracts and procedures sit in shared drives built for people to browse. Point a generic chatbot at them and it guesses, mixes versions or shows people documents they should not see. An assistant your teams can rely on has to answer only from approved sources, show where each answer came from and respect every permission.
Each one answers from approved sources and shows where every answer came from.
Staff get instant answers on leave, benefits, travel and procedures.
Teams find clauses, obligations and precedents across contracts in seconds.
Agents and AI answer customers consistently from the latest product and policy information.
Technicians and operators get step-by-step answers from manuals and procedures.
Compliance teams search regulations, circulars and internal controls with cited answers.
Sales teams find pricing rules, product details and proposal content fast.
Good answers depend on what happens before and after the model writes them.
Reads documents of every format, splits them sensibly and keeps them up to date as they change.
You get: Always the latest version
Finds the most relevant passages using search and your ontology’s business terms.
You get: The right passage, not a near miss
Applies your existing permissions, so people only get answers from documents they can open.
You get: No leaks across roles
Writes a clear answer from the retrieved passages and cites each one.
You get: Every answer has a source
Tests the assistant against real questions with known answers, before go-live and after every change.
You get: Accuracy measured, not assumed
Collects user ratings and unanswered questions and turns them into fixes.
You get: Better every week
Tell us which documents and systems hold the answers. We’ll show you how we would build an assistant your teams can trust.
Generic search matches words. Our assistants use your ontology to understand what people mean: that "SPA", "sale agreement" and "contract" are the same thing, which project a unit belongs to, and which policy applies to which customer type.
Each new assistant reuses the same connectors, permissions and testing.
One assistant for one team, connected to its documents, tested and live in Teams.
We run your assistants and add new teams, sources and use cases.
Repair manuals, service bulletins and past job cards searchable in plain language, with each answer citing the page it came from.
One assistant brought the mall’s services together and answers visitor questions from approved information, handing the rest to staff.
About enterprise RAG
Copilot is excellent for personal productivity across your Microsoft 365 content. Our knowledge assistants are built for a specific job and question set, can combine documents with ERP, CRM and data platform records, use your business terms, and are tested for accuracy against real questions before go-live. They can also run inside Copilot Studio and Teams.
Fine-tuning changes a model’s behavior by training it on examples; RAG leaves the model unchanged and gives it the right passages from your documents at the moment of the question. For enterprise knowledge, Data Semantics uses RAG because answers stay current as documents change, every answer can cite its source and permissions can be enforced per user.
Yes. Data Semantics combines documents with records from ERP, CRM and your data platform, so an assistant can answer questions such as what a contract says about late payment and how much that customer currently owes, in one reply with both sources cited.
Accuracy and security
It answers only from retrieved passages and cites them; if it can’t find an answer it says so and routes the question to a person. We test it against real questions with known answers before launch and after every change.
No. The assistant applies your existing permissions, so each user only gets answers drawn from documents and records they already have access to.
Sources are re-indexed automatically as documents are added, changed or retired, superseded versions are excluded, and the assistant is re-tested against its question set after every significant change.
Content and languages
Assistants can be built for English and Arabic questions and documents. We test language quality as part of the pilot.
Platforms and deployment
Data Semantics builds on Azure AI Foundry and Azure AI Search with Azure OpenAI, Anthropic Claude and open-weight models such as Llama, Mistral, Qwen and DeepSeek, and on Copilot Studio where Microsoft 365 integration matters. The model is chosen per use case for accuracy, cost, language and where the data must stay.
Yes. Knowledge assistants can run in your own tenant or, for banks and other regulated organizations, in a private or on-premises deployment.
Results
By answer accuracy on a test set, how often people use it, how many questions it resolves without an expert, and the time saved per question.
Bring us one team and its documents. We’ll show you an assistant that answers it, with sources, tested on your real questions.
