AI solutions
AI systems that sit inside a business process
Raab Group builds AI where it removes a specific task: answering from your own material, assisting a member of staff, or moving work through a process. The model is one part. Permissions, evaluation, and a person who can take over are the rest.
- A defined job
- Sources you control
- Permissions kept
- A person can take over
What we will and will not propose
We propose AI when the inputs exist, the cost of a wrong answer is understood, and someone owns the workflow. We do not propose a chatbot as a substitute for a missing knowledge base, and we do not promise that a model will be correct because the demo looked fluent.
How this relates to software delivery
An assistant that cannot read your CRM, or a bot that cannot hand a booking to a person, is a toy. AI work here is delivered as software: APIs, audit, environments, and a release you can turn off.
AI with a job
The assistant is allowed to
- Answer from sources you name
- Draft for a person to send
- Create a task a human owns
A person still does
- Move money or change a contract
- Invent policy
- Run with no way to take over
What changes an AI engagement
The job
A chatbot, a retrieval assistant, and an automation are different systems. We pick one first.
The sources
If the documents and permissions are unclear, the model is not the hard part.
The takeover
Every flow needs a point where a person can see what happened and continue.
What an AI brief has to include
- 01
The job
Answer, draft, or take a defined task. Pick one first.
- 02
The sources
The documents or records it may use.
- 03
The limit
What it must not change: money, contracts, or policy.
- 04
The person
Who takes over, and where they see the thread.
Marks an AI piece is allowed to run
- 01
The task is named
The model is doing one job a person can describe, not “adding AI”.
- 02
A person can override
Staff can correct or stop the output before it becomes the record.
- 03
The source is known
Answers and drafts point at the document or the field they came from.
- 04
The cost is visible
Someone can see what a week of calls costs before it is left on in production.
AI practices
Generative AI
Drafting and summarising tied to your content and your rules.
LLM development
Model integration, tools, evaluation, and operational limits.
RAG development
Answers grounded in your documents, with permissions intact.
AI agents
Task runners with tools, limits, and an audit trail.
AI chatbot development
Website, WhatsApp, and desk bots that know when to stop and hand over.
AI assistants
In-product help for staff, grounded in the systems they already use.
Conversational AI
Multi-turn dialogues with state, memory limits, and a way out.
