AI could help you.
But where exactly?
Adding AI everywhere serves no purpose.
The better question is: in which processes can it save time, improve access to information or help teams without complicating their work?
Slash starts from the problem, not the technology.
The method
Start from the need, not from AI.
Before choosing a model or a tool, we seek to understand:
- Which task takes time
- Who performs it
- What information is used
- Which decisions require human judgement
- What data is available
- What risks exist
- How to verify the quality of the result
AI then becomes one possibility among others.
The use cases
Concrete use cases.
Searching your documents
Let a team find information more easily in a document base, procedures or files.
Content preparation
Help structure, summarise or prepare content that is then validated by a person.
Qualifying requests
Analyse or categorise certain requests before the team handles them.
Information extraction
Identify and structure data found in unstructured documents or content.
Internal assistance
Help employees reach the information they need for their work more quickly.
AI-enriched automation
Use AI in one precise step of a workflow rather than as an isolated solution.
The limits
When AI is not the right answer.
Some problems are better solved with:
- A clean database
- A better interface
- A classic business rule
- A deterministic automation
- An integration between two tools
- Better organisation of information
Using a more complex technology is not automatically an improvement.
The framing
The questions to answer before building.
- What data can be used?
- Is the information sensitive?
- What level of error is acceptable?
- Is human validation necessary?
- How do we measure whether the tool really saves time?
- What happens when an answer is wrong?
- Which provider or model is appropriate?
- How does the tool fit into the existing work?
The integration
AI + business software.
AI often becomes more useful when it is integrated into a real working tool. Rather than an isolated chatbot, it can be a function built into:
- A client portal
- An internal tool
- A document system
- A workflow
- A business application
- A qualification or reporting process
When development is justified, it joins our work in web applications and process automation, with ongoing digital support.
The questions we get asked.
Straight answers, before we even talk.
Another problem to solve?
Too much still done by hand?Need a client portal?Your website generates few enquiries? Does an SME really need AI?
Not necessarily. AI is relevant when it solves a specific problem better than a simpler solution. The goal is not to use AI, but to improve a process or a result.
Can you add AI to our existing tools?
It depends on the systems used, their integration options and the available data. It is a point to verify during the diagnosis.
Do we need to train our own model?
In most SME projects this is not necessarily required. Existing models can often be integrated and adapted to the context of the company.
What happens with sensitive data?
Confidentiality, access, storage and the providers used must be examined before any integration. These constraints can strongly influence the architecture of the solution.
Have an idea for using AI?
Tell us about the problem you are trying to solve. We will then determine whether AI is really the right answer.
Talk it through with Slash