Ask a question, get theright document.
Type a question and get the answer from your own documents, with the original file and exact page, without hallucinations. A safe internal AI for your whole organisation, connected to SharePoint, OneDrive and every other storage location.
- Inside your own Azure
- The internal AI runs through Microsoft Foundry within your Azure environment, so your documents are not sent to third parties.
- Answers without hallucinations
- The internal AI answers questions and finds documents, both from your own files, and gives you the original document at lightning speed.
- Down to the exact page
- In a long manual, contract or report, the search takes you straight to the page that holds the answer.
The problem
When the answer is buried in millions of documents
Organisations hold millions of documents across countless SharePoint sites, OneDrive folders and file shares, and people still cannot find what they need. Today, one question in plain language is enough to reach the right document, down to the exact page.
Common symptoms
Keyword search returns long lists of files, and the right one is rarely at the top
People first have to guess which of dozens of SharePoint sites or folders holds the file
Once the right file turns up, the answer is still buried on one page of a long document
What this costs you
Searching, opening and scrolling take time out of every working day
People give up and ask a colleague, or rewrite a document that already exists
Knowledge your organisation already wrote down goes unused because nobody can find it
How AI Document Search works
From millions of files to the right answer, with its source
Three parts turn millions of stored files into an internal AI the whole organisation can ask: every storage location connected and made searchable, an internal AI that runs safely in your own Azure, and answers that always point to their source.
Documents made searchable
Focus
We connect SharePoint, OneDrive and any other place your documents are stored, even on-premise, and build a connector where none exists. Then we vectorise the documents, so the AI can search them by what they say and find the exact passage and page, not only the file.
Key outputs
A list of connected sources, a vector index of their documents, and the agreed way new and changed files are added.
An internal AI in your own Azure
Focus
We set up Microsoft Foundry in your Azure environment with the AI model you choose, and connect it to the document index. Staff ask in plain language, and because everything runs within your own environment, your documents are not sent to third parties.
Key outputs
Microsoft Foundry set-up, the internal AI connected to the document index, and the architecture documentation.
Answers with their source
Focus
Every answer is drawn from your own documents and links to the original document and the page it came from. That keeps answers free of hallucinations and lets anyone check the source in one click. Courses in AI usage show staff how to ask a good question.
Key outputs
Answers with source links to document and page, courses in AI usage and handover documents.
Capabilities
What we deliver
What AI Document Search includes, from the connection to your storage to the answer on screen. Each part is in the package, not an extra.
Connectors to every source
SharePoint, OneDrive, file shares and other document stores, in the cloud or on-premise. Where no standard connector exists, we build one.
Vectorisation of documents
Documents are turned into vectors, so the AI finds them by what they say, not by file name or exact keyword.
Search within documents
The search reaches inside long documents and points to the exact page, like finding the right page in a book.
Internal AI
Staff ask in plain language and get an answer from your own documents, with the original document linked.
Microsoft Foundry in Azure
The AI model of your choice is managed in a controlled way through Microsoft Foundry, set up in your own Azure.
Courses in AI usage
Staff learn how to ask a good question and how to check the source behind an answer.
Where it creates value
Who benefits most
Practical value for the teams that carry the most complexity.
Legal and procurement
Teams that need the right clause, contract or policy without reading through dozens of files.
- Ask what a contract says about notice periods and go straight to the clause
- Find the policy or template that applies to a question
- Rely less on the one colleague who knows the archive
Finance and control
Controllers who need the agreement, memo or report behind a number.
- Find the supporting document for an auditor or board question
- Ask what an earlier memo or report concluded, with the source linked
- Fewer questions to colleagues about where something is filed
Operations and projects
Teams working from procedures, manuals and earlier project files.
- Ask how a task is done and get the right page of the manual
- Reuse earlier project documents instead of starting from scratch
- New staff find answers in the files without a guide
HR
HR teams answering the same questions about policies and regulations again and again.
- Staff ask about a policy and get the answer with the document
- One place to ask, wherever the document is stored
- HR time goes to questions that really need a person
IT and data
IT and data teams who want one safe AI for documents, inside their own environment.
- Fewer requests to track down a document
- The model runs through Microsoft Foundry in your own Azure
- One documented set of connected sources, cloud and on-premise
Less relevant if...
AI Document Search is a weaker fit in these situations.
- You want incoming documents processed and passed on automatically (Document Automation fits better)
- You need answers that combine documents with figures from databases such as Fabric, Databricks or SQL (AI Company Brain fits better)
- Your document library is small and people already find what they need
How it works
A practical delivery approach
Every engagement follows a clear path from diagnosis to delivery and handover.
Scope
We agree which storage locations are included, such as SharePoint sites, OneDrive folders or on-premise file shares, who will use the internal AI and which questions it must answer. Those questions become the benchmark for acceptance.
A scope document with sources, users and key questions, and a fixed-price proposal for the first phase.Design
We design how each source is connected and kept up to date, how the documents are vectorised, and how Microsoft Foundry and the chosen model are set up in your Azure environment.
Architecture design and agreed acceptance criteria.Build and test
We connect the sources, vectorise the documents and set up the internal AI, checking answers and source links against the agreed questions as we build.
A working internal AI in your Azure environment, with test results.Acceptance
You sign off the internal AI against your real questions: each one answered from your own documents, with the right document and page linked. Anything not yet right is fixed before go-live.
Sign-off against the agreed questions.Hypercare and handover
After go-live, staff take the courses in AI usage, we stay on hand during hypercare to resolve issues and fine-tune the answers, and your team receives the documents it needs to run the internal AI.
AI usage courses, a hypercare period and handover documents.
Proof & trust
Results that speak for themselves
Inside your own Azure
The internal AI runs through Microsoft Foundry within your Azure environment, so your documents are not sent to third parties.
Answers without hallucinations
The internal AI answers questions and finds documents, both from your own files, and gives you the original document at lightning speed.
Down to the exact page
In a long manual, contract or report, the search takes you straight to the page that holds the answer.
Every storage location connected
SharePoint, OneDrive and any other place your files are stored, even on-premise, searched with one question.
Staff trained in AI use
Courses in AI usage show staff how to ask for what they need and how to check the source.
A usable result every phase
Each fixed-price phase ends with live results, a demo and handover documents.
Example engagement
What it looks like when it works
How an engagement like this typically runs. An illustration, not a client result.
Context
Example: a large organisation whose contracts, policies, manuals and project files are spread across many SharePoint sites, OneDrive folders and an on-premise file share.
Challenge
Staff search by file name or ask colleagues, then read through long documents to find the passage they need. The organisation wants an internal AI for this, but only if its documents stay in its own environment and every answer can be traced to its source.
Solution
Scoping selects the sources and the questions that matter most. SolvX sets up Microsoft Foundry in the client's Azure environment, connects SharePoint, OneDrive and the file share, vectorises the documents and puts an internal AI on top that answers with the original document and page linked. Staff take the courses in AI usage.
What you get
Connected document index
The documents from SharePoint, OneDrive and the on-premise file share, vectorised and kept up to date.
Internal AI on Foundry
Answers in plain language with the source document and page linked, running within the client's own Azure environment.
Courses and handover pack
Courses in AI usage for staff and the handover documents for the client's team.
Context
Example: a large organisation whose HR and operations teams keep answering the same questions about policies, procedures and manuals that sit in SharePoint.
Solution
A first fixed-price phase covers only the HR and operations libraries. Those documents are vectorised, staff ask the internal AI what a policy or procedure says and go straight to the right page, and the courses in AI usage show them how to ask a good question. The next sources are scoped once the first phase has been accepted.
What you get
Searchable policies and manuals
Staff ask in plain language and get the answer with the right page of the policy or manual.
Courses in AI usage
Courses that show staff how to ask a good question and check the source.
Scope for next sources
A scoped proposal for connecting further sites and storage locations in a following phase.
Frequently asked questions
Your questions, answered
An internal AI that answers questions and finds documents across the sources agreed in scoping, such as SharePoint, OneDrive and other storage locations, even on-premise. It runs on Microsoft Foundry in your Azure environment, with your documents vectorised so it finds the right file and the exact page. Around that: courses in AI usage, a hypercare period after go-live and handover documents for your team.
Answers are drawn from your own documents, not from what the model happens to know, and each one links to the original document and the page it came from. That keeps answers free of hallucinations, and anyone can open the source in one click to check.
Yes. Documents are vectorised passage by passage: each passage becomes a vector, a numerical representation of what it says. A question is matched to the passages that answer it, even when it uses different words, so the AI takes you to the exact page in a long manual, contract or report.
The internal AI runs through Microsoft Foundry within your own Azure environment, so your documents are not sent to third parties. You choose the AI model. Azure is our standard, but the internal AI can also be built in another environment you use. Which sources are included is agreed in scoping.
AI Document Search is built for documents: it answers questions from your files and finds the right document and page, wherever they are stored. AI Company Brain is wider: a personal AI workspace for every employee, on one linked company brain of documents, notes and data from databases such as Fabric, Databricks or SQL. If the need is answers from documents, Document Search is the focused choice. If people also need answers from your data, look at AI Company Brain.
A business owner for the internal AI, access to your Azure environment and to the storage locations in scope, and a list of questions people often ask. Those questions are what the internal AI is built and signed off against.
The build is bought as fixed-price phases, each scoped up front and ending with live results, a demo and handover documents. After hypercare, support can continue under Managed Services, as an SLA or a subscription. Extra advice or changes outside the agreed scope can be billed by the hour. You receive a fixed price after scoping.
Everything is built in your own environment: the internal AI and its index run in your own Azure, and your documents stay where they are stored today. Each phase ends with handover documents so your team can run it. You own your data, your client-specific code and the documentation. SolvX keeps the rights to its generic building blocks; the contract sets out the details.
When incoming documents need to be processed and passed on automatically, that is Document Automation. When people need answers that combine documents with figures from Fabric, Databricks or SQL, AI Company Brain fits better. And when the library is small and people already find what they need, this package adds little.
Next step
Where do you want to start?
Pick the path that matches where you are today. Both begin with a conversation.
Ready to ask your documents a question?
Start with a conversation about your documents. We look at where your files are stored, which questions people need answered and which sources to start with, and explain how a fixed-price first phase and the support after it are set up.
- Map where your documents are stored and who needs them
- Choose the sources and questions for a first phase
- Understand how the build and the support afterwards are bought
No obligation. Typical response within 1 business day.
Start with an assessment
Not ready to commit to a pilot? A 2 to 4 week assessment maps your current state and identifies the highest-value starting point, with no obligation to proceed further.
- Map your current situation and pain points
- Identify 2 to 3 high-value improvement opportunities
- Get a recommended pilot scope and expected outcomes
No obligation. Typical response within 1 business day.
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