Interconnectedcompany knowledge
One central brain that links everything your company knows, and a personal AI workspace for every employee. Each person works with their preferred AI on all the knowledge they are allowed to see. Every bit of new knowledge from each employee gets added to the brain with their permission on the go.
- A personal AI for everyone
- Every employee gets their own workspace to work with their preferred AI on company knowledge.
- Access by security group
- Everyone reaches all the information they are allowed to see. Security groups on the files decide who sees what.
- Your own Azure environment
- The company brain and every personal workspace run in your own Azure environment, under your own security rules.
The problem
Everyone uses AI with no access to shared knowledge
What your company knows is spread across SharePoint, OneDrive, databases and the heads of a few colleagues, and none of it is connected. Staff already use AI, but each in their own tool, without the company's knowledge behind it, and nobody controls who sees what.
Common symptoms
Every employee uses a different AI tool, and none of them knows your company
Documents, figures and notes on the same topic sit in different systems, and nobody sees how they connect
Connecting AI to company files raises the obvious fear: will everyone suddenly see everything?
What this costs you
Staff paste company documents into public AI tools because there is no approved alternative
Answers miss half the picture, because the AI only sees the one file someone uploaded
Knowledge leaves with the people who hold it, and every new colleague starts from zero
How AI Company Brain is built
Built on one shared company brain
AI Company Brain has three parts: a central brain that links your company's documents and data, a personal AI workspace for every employee, and access rules that follow your security groups.
One central company brain
Focus
A central environment for the whole company that holds shared documents, notes, vectorised tables and other structured and unstructured information. It works like a linked knowledge base: each piece is connected to what it relates to, so the AI works with context instead of loose files.
Key outputs
The central brain on the sources agreed in scoping, from SharePoint and OneDrive to Fabric, Databricks or SQL, kept up to date.
A personal AI workspace for everyone
Focus
Every employee gets their own workspace, in a container of their own, to talk and work with their preferred AI. Each workspace draws on the central brain, so everyone works from the same company knowledge.
Key outputs
Personal AI workspaces for the agreed user groups, with the AI models chosen in scoping.
Access by security group
Focus
Files and data in the brain carry security groups, and every workspace respects them. Everyone can reach all the information they are allowed to see, and the AI only answers from what that person may see.
Key outputs
An access design based on your security groups, agreed with IT and security, and handover documents.
Capabilities
What we deliver
Everything AI Company Brain needs, from the central brain to the workspace on every desk.
Central company brain
One central environment where shared documents, notes and vectorised tables are stored and linked to each other, so related knowledge is found together.
Personal AI workspaces
A workspace for every employee, in their own container, where they work with their preferred AI on company knowledge.
Security groups on every file
Access follows the security groups you already manage, so each person and their AI only reach what they are allowed to see.
Connections to your sources
SharePoint, OneDrive, Fabric, Databricks, SQL, your ERP or CRM: we connect the systems you run, and build a connector where none exists.
Documents and data together
Documents and notes next to the tables from your databases, all vectorised, so the AI finds text and figures by what they mean, not by keyword.
Courses in AI usage
Courses that help your staff get the most from their own AI workspace and the shared company brain.
Where it creates value
Who benefits most
Practical value for the teams that carry the most complexity.
CIOs and IT
Leaders who want to give everyone AI without losing control of company data.
- One approved AI workspace per employee, instead of a different tool per team
- Access that follows the security groups you already manage
- Everything running in your own Azure environment
- Handover documents, so your team knows what was built
Data teams
Teams with data in Fabric, Databricks, SQL or another platform that the business keeps asking about.
- Tables vectorised into the brain, so business users find figures themselves
- Fewer requests from colleagues looking for a figure or a file
- Documents and data linked, so an answer shows the figure and the context behind it
- An AI set-up that builds on the data platform you already have
Managers and business users
People who need knowledge from across the organisation but do not know where it sits.
- Their own workspace on company knowledge, with their preferred AI
- Answers that combine documents, notes and figures on the same topic
- Questions asked in plain language, in Dutch or English
- Knowledge from colleagues and other regions, as far as they are allowed to see it
Less relevant if...
In these cases another route fits better.
- The data behind your questions is not yet reliable. Start with AI Readiness instead
- You only need answers and the right document from your document stores. AI Document Search is built for that
- Incoming documents need to be processed automatically. Document Automation fits better
- You do not want it to run in your own Azure environment
How it works
A practical delivery approach
Every engagement follows a clear path from diagnosis to delivery and handover.
Scope
We agree which knowledge goes into the brain first, which documents and databases it comes from, which user groups get a workspace and which AI models fit your rules on data.
Agreed scope, source list and user groups, with a fixed price for the next phase.Design
We design the central brain, the personal workspaces and the access model in your Azure environment, based on the security groups you already use.
An architecture and access design, agreed with your IT and security teams.Build and test
We set up the brain and the workspaces, connect and link the sources, and test answers and access rights against the agreed questions as we build.
A working AI Company Brain in your Azure, with its test results.Acceptance
You sign off against the agreed questions: each one answered from the right sources, and each user seeing only what their security groups allow. Anything not yet right is fixed before go-live.
Sign-off against the agreed questions and access rules, and a go-live decision.Hypercare and handover
After go-live, staff take the courses in AI usage, we stay on hand during hypercare to resolve issues, and your team receives the handover documents.
Trained users, handover documents and an agreed route for further support, by subscription or SLA if you want it.
Proof & trust
Results that speak for themselves
A personal AI for everyone
Every employee gets their own workspace to work with their preferred AI on company knowledge.
Access by security group
Everyone reaches all the information they are allowed to see. Security groups on the files decide who sees what.
Your own Azure environment
The company brain and every personal workspace run in your own Azure environment, under your own security rules.
One linked company brain
Shared documents, tables and notes sit in one central brain, linked to each other, so an answer brings the related knowledge with it.
Documents and data together
Structured and unstructured information side by side, from files and notes to vectorised tables from your databases.
Any AI model
Everyone works with the AI model they prefer, and you can switch when a better one arrives.
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 with its documents in SharePoint and OneDrive, its sales figures in Microsoft Fabric and a growing number of staff using their own AI tools.
Challenge
Knowledge about the same customer or project sits in several places, and each AI tool sees only what someone pastes into it. IT wants one approved route, and HR and finance files must stay visible to their own teams only.
Solution
A typical engagement starts by scoping the knowledge and user groups that matter most. SolvX then builds the central brain in the organisation's own Azure environment, links the SharePoint and OneDrive documents to the vectorised Fabric tables and gives each employee in scope a personal AI workspace. Access follows the existing security groups, and staff take courses in AI usage.
What you get
One linked company brain
The documents from SharePoint and OneDrive and the Fabric sales tables, linked in one central brain
A personal AI workspace each
A workspace for every employee in scope, with the AI models chosen during scoping
Access by security group
HR and finance knowledge visible only to the groups allowed to see it, agreed with IT and security
Context
Example: an organisation operating in several regions, where each region keeps its own documents and reports and managers cannot see what the others know.
Solution
A typical engagement links the regional SharePoint sites and the central Databricks data in one company brain, with access per region and role agreed in the design. Managers work in their own AI workspace and draw on the knowledge of other regions wherever they are allowed to see it.
What you get
Regions linked in one brain
The regional SharePoint sites and the central Databricks data, linked in one central brain
Access per region and role
Which groups may see which knowledge, agreed with IT and security during design
Courses in AI usage
Courses for managers and their teams, so they use their workspace in their own work
Frequently asked questions
Your questions, answered
It has two parts that work together. A central company brain holds your shared documents, notes and vectorised tables, linked to each other like a knowledge base. Every employee gets a personal AI workspace in their own container, where they work with their preferred AI on that knowledge. A public AI tool only sees what someone pastes into it and works outside your organisation. AI Company Brain works on your own linked knowledge, in your own Azure environment.
No. Files and data in the brain carry security groups, usually the ones you already manage. Each person, and the AI working for them, can reach all the information their groups allow and nothing else. The access design is agreed with your IT and security teams before anything is built.
Structured and unstructured information from the systems you already run, standard or custom-built: document stores such as SharePoint and OneDrive, databases such as Microsoft Fabric, Databricks or SQL, and business systems such as your ERP or CRM. Documents and tables are vectorised and linked in the brain. If there is no standard connector for a system, we build it ourselves. During scoping we agree which sources go in first, so the first phase stays focused.
Whichever models your people prefer, and you can add or switch models later as AI moves on. Which models fit, and where they run, is settled during scoping against your rules on data.
The AI answers from the knowledge in your brain, and because documents, notes and tables are linked, it works with the context around a fact, not one loose file. We test the answers against the agreed questions while we build and before go-live. A wrong number in an AI answer can create real liability, so we also agree where a person checks an answer before anyone acts on it.
Your own Azure environment, or the decision to set one up with us. Access to the documents and databases in scope, and to your security groups. A business owner who decides what goes into the brain, contacts in IT and security for the access design, and the users who take the courses in AI usage.
The build is bought in fixed-price phases, each agreed after scoping, so you know what a phase costs before it starts. After hypercare, support can continue under Managed Services, as an SLA or a subscription, and extra advice or changes can be bought by the hour. The Azure usage itself runs on your own Microsoft bill.
You own your data, the knowledge in your brain, your client-specific code and the documentation. SolvX keeps the rights to its generic building blocks; the contract sets out the details. AI Company Brain runs in your own Azure environment, and each phase ends with handover documents that describe what was built and how it works.
When the data behind your questions is not yet reliable, start with AI Readiness. When you only need answers and the right document from your document stores, AI Document Search is built for that. When incoming documents need to be processed automatically, Document Automation fits better. And if you do not want it to run in your own Azure environment, this package is not for you.
Next step
Where do you want to start?
Pick the path that matches where you are today. Both begin with a conversation.
Give every employee an AI that knows your company
Start with a scoping conversation. We look at where your company knowledge sits today, who needs which part of it and your rules on data, and propose a first fixed-price phase.
- Map where your knowledge sits and how it connects
- Agree which teams get a workspace first and what they may see
- Receive a fixed-price proposal for the first phase
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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