When do you choose custom AI software?
Choose customization when the value of time savings, error reduction or new functionality is higher than the development cost. For casual writing tasks, a standard tool is enough. For recurring processes with data, decision rules and integrations, customization is often stronger.
When do you first need an AI consultant?
You first need a Hire Jan Kenis as an AI consultant when the problem is not yet clear enough to build software. Consultancy helps determine which users, data, risks, integrations and measurement points are needed before a development process starts.
What can you have built?
AI software can be internal, customer-facing or supportive.
| Type | Example |
|---|---|
| Internal knowledge seeker | AI that searches documents, manuals and files |
| Quotation help | AI that summarizes requests and prepares draft quotes |
| CRM connection | AI that enriches leads and automatically creates tasks |
| Customer-oriented function | An AI assistant within your own website or portal |
How does a process proceed?
A good process starts small. First we determine the problem, the data, the users and the risks. Then we build a prototype that solves a real task. Only when that works will we continue to build on links, rights, logging and management.
From practice
Many customized questions appear to be partly solvable with existing building blocks. By combining smart components with targeted customization, the costs remain manageable and the solution maintainable.
What data and links are needed?
The required data depends on the process. Sometimes documents and forms are sufficient. Sometimes API links with CRM, invoicing, planning or website are necessary. We assess in advance which data is reliable enough and which information should not be processed by AI.
Which AI software applications are suitable for companies?
Suitable applications have recurring usage, clear users and data of sufficient quality. AI software works better when it supports a concrete task than when it becomes a generic chatbot without a purpose.
These applications often recur.
- An internal knowledge seeker based on manuals, cases and procedures
- A quotation aid that summarizes requests and prepares next steps
- A lead assistant that combines forms, CRM data and follow-up
- A customer portal with AI support for questions or document analysis
- A content or reporting tool that converts data into verifiable output
What is RAG in AI software?
RAG stands for retrieval augmented generation. This means that AI first retrieves relevant information from your own documents, database or knowledge base and only then prepares an answer or action. For companies, RAG is useful when AI needs to work with internal knowledge without freely guessing.
RAG is especially useful for these applications.
- An internal knowledge assistant for manuals, quotations and procedures
- A support assistant that bases answers on existing documentation
- A quotation aid that retrieves conditions, cases and product information
- A search function in documents, contracts or project files
What integrations make AI software more valuable?
AI software becomes more valuable when it is linked to the systems your team already works in. Without integrations, AI often remains a separate tool. With integrations, AI becomes part of the process.
These integrations are often useful.
| Integration | Why useful |
|---|---|
| CRM | AI can combine lead information, customer status and follow-up |
| Website or portal | AI can help customers or employees within your own environment |
| Document storage | AI can search in procedures, quotations, manuals or files |
| Planning or project software | AI can prepare tasks, deadlines and context |
What is the difference with AI automations?
Build AI automations mainly connect existing tools and steps. Custom AI software builds its own interface, logic or product function. A process often starts as automation and grows into software when the workflow becomes important enough.
How do you limit the risk?
Limit risk by starting with a defined case, clear evaluation criteria and human control on critical output. For many companies, a prototype is the best first step. Discuss your idea via a free discovery call.