AI that works inside your company, not just in a chat window.
Your team already uses AI chats, but everyone on their own, often pasting company data into them. An implementation connects AI to your systems and documents, with clear data access rules, a spending limit and a person’s approval before anything reaches a client or a system.
- Prototype on your own data before you commit
- 50,000+ documents handled by AI in production
- 2 working days to a quote after the call
AI is in the company, but without a plan.
- 01
Everyone uses AI their own way
Contracts, e-mails and client data end up in free chat tools. Nobody knows where that information stays or whether the result was right.
- 02
Knowledge scattered across folders
Procedures, price lists and answers to common questions sit on drives and in inboxes. New people ask colleagues, and experienced staff answer the same questions again and again.
- 03
An inbox full of requests
Enquiries, complaints and orders arrive at one address. Someone has to read, assess and pass them on before the real work can start.
- 04
A pilot that stayed a demo
The first try with AI looked good in a presentation, but it never connected to company systems and nobody uses it day to day.
An AI assistant that knows your company documents.
People ask the way they would ask an experienced colleague. The assistant searches terms, contracts, price lists and ticket history, puts together an answer and points to the document behind every piece of it. It only sees what the person asking has access to.
Where AI takes load off your team.
Company knowledge
- An assistant that answers from procedures, contracts and price lists
- Search across documents by meaning, not just keywords
- Answers that point to their source
- Permissions, so everyone sees only what they have access to
E-mail and requests
- Classifying e-mails, enquiries and complaints
- Routing each case to the right person or system
- Draft replies for approval
- Summaries of long threads and calls
Data and documents
- Reading invoices, contracts and forms
- Data from e-mails and PDF files moved into your system
- Reports and summaries prepared automatically
- AI agents taking the next steps of a process under human supervision
From one task to a working implementation.
- 01 first task chosen
Call and choice of task
Which task takes your team the most time and where AI pays off fastest. The implementation starts there, not with picking a model.
- 02 prototype
Prototype on your data
A first version on a sample of real e-mails, documents or questions. You see accuracy and cost before deciding on the full rollout.
- 03 rollout
Rollout in the process
Connection to e-mail, drives, CRM or ERP, plus a panel where your team approves and corrects results.
- 04 growth
Monitoring and growth
Accuracy and cost monitoring, improvements based on real use and further tasks for AI.
What an AI implementation costs.
The cost depends on the task, the amount of data and the systems AI has to work with. After a free consultation you get a staged quote within 2 working days, with an estimate of the monthly AI model cost.
Always included
- Prototype on a sample of your data
- Approval and correction panel
- AI spending limits and cost control
- Documentation and full access to the code
- Team training
What affects the price
- Type of task and amount of data
- Systems AI connects to
- Number of users and permission levels
- Data and GDPR requirements
- How much of the output your team reviews
Proven models, decisions left to people.
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Large language models
Gemini, GPT, Claude or the European Mistral, chosen for the task and the cost. They run in a mode where your data is not used to train the model.
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Company knowledge (RAG)
AI answers from your documents and data rather than general knowledge from the internet. Every answer shows its source.
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A person approves
Results that change anything in your systems wait for your team to accept them. AI prepares, and your team has the final say.
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Predictable cost
Spending limits and a model matched to the task keep the monthly AI bill from growing unchecked.
Projects that speak for themselves.
Questions about AI implementation.
Yours is not here? Ask during the consultation or send a message.
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For writing and brainstorming it often is. An implementation makes sense when AI has to work on company data, connect to its systems and run inside a process without copying and pasting. A company assistant or chatbot on your own data answers from your documents, respects permissions and connects to your systems.
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Models run through an API in a mode where data is not used for training, and through cloud services in an EU region wherever possible. Documents and the knowledge base stay in infrastructure on your own account, and a data processing agreement is standard.
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They don’t have to be perfect. The assistant works with files where they already are, for example on a drive, in SharePoint or in a CRM. The prototype shows which documents are out of date or contradict each other, and those are the ones worth tidying first.
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The assistant answers from the version stored in the knowledge base, which is refreshed along with the sources, automatically or on an agreed schedule. Every answer points to its document, so it is easy to check where it came from.
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Every model sometimes gets things wrong, so the assistant answers from passages found in your documents and shows the source with every answer. When the documents hold no answer, it is set up to say so instead of guessing. Results that change anything in your systems are approved by a person, and the prototype shows accuracy on your own data before you decide.
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AI that carries out the steps of a task on its own, for example reading a request, checking data in a system and preparing a reply. In a company it works within agreed limits, and a person approves the important steps.
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That is not the point. AI takes over reading, sorting and retyping, and people handle decisions, exceptions and contact with clients.
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With a free 30-minute call about one task that takes your team the most time. For the call, a description of how the work is done today is enough, and for the prototype a few sample e-mails, documents or questions with sensitive data removed.
The first step is a 30-minute call.
No fees and no strings attached. Describe what you want to build or improve. Within 2 working days you get a quote and a plan, or an honest note that a simpler solution will do.