MaalariPro
AI-assisted estimating and document workflows for painting and construction work.
AI inside the systems you already use.
We build AI features connected to your own data and workflows: AI assistants, knowledge-base chatbots, document processing and integrations into existing software.
01 What we build
Typical AI solutions
Company AI assistant
Answers staff questions from your own guidelines and documents, with sources shown.
Customer service chatbot
Handles the most common questions and hands the rest to a person.
Knowledge base and search (RAG)
Documents are indexed so the model answers from them, not from general knowledge alone.
Document processing
Extracts data from quotes, invoices, contracts or forms into a structured format.
Automations
Recurring steps such as classification, summarising, routing and drafting.
AI in existing software
Search, summaries or suggestions added to a system you already use, through an API.
02 Assistant or agent
When do you need an AI agent?
When AI needs to answer, search or summarise, an assistant or integration is usually enough. When it has to act in your systems across several steps, you need an AI agent — and permissions and oversight matter more.
AI agents03 Principles
How an AI solution stays reliable
Sources visible
The basis for an answer is shown so it can be checked.
Your data under control
We define what data is processed, where and on what terms.
Measurable benefit
The solution is compared with the current way of working before it is expanded.
People decide
AI suggests and prepares; important decisions are made by people.
Related work
AI Publishing
A workflow that turns source material into a structured book manuscript.
How a project runs
Six phases, the same people.
- 01
Definition
Goal, users, constraints and the smallest useful first release.
- 02
Design
User flows, data model, architecture and interface are designed before the build.
- 03
Build
Built in short iterations, with a working version visible throughout.
- 04
Testing
Automated tests, accessibility and security are checked before release.
- 05
Release
Deployment, monitoring and, where needed, migrating data from the old system.
- 06
Ongoing development
Fixes, improvements and new features based on real use.
AI solutions FAQ
- What is a company AI assistant?
- An AI assistant is a language-model-based tool that answers questions from your own documents and guidelines. A well-built assistant shows which source an answer comes from, so it can be verified.
- What does RAG mean?
- RAG (retrieval-augmented generation) means the model first retrieves the relevant passages from your own material and then answers based on them. Answers are grounded in current information rather than only the model's general knowledge.
- Can AI be added to existing software?
- Often, yes. An AI feature can be connected to your current system through an API without rebuilding the whole application.
- Is the AI model trained on our data?
- Usually that is not needed. Most solutions retrieve information from your material at the moment of the question, so the model is not trained on your data. The model provider's data processing terms are reviewed at the start of the project.
- How much does an AI solution cost?
- It depends on scope and integrations. Language model usage also has running costs, which are estimated in advance. You get an estimate before development starts.
Related services
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Where could AI help in your work?
Tell us which information is searched for by hand or which document work keeps repeating.
Tell us about your project