CaseAI and search9 min
Semantic search and intent-based systems
What is semantic search? How vector and hybrid search work in Meilisearch, what they do for online shops and chatbots, and how we build it in Laravel.
AI and automation
AI and automation for businesses
We connect AI models to the systems you already use, and build tools that take over dull but important work in production. Traceability and access control are there from day one.
- RAG, AI agents and copilots
- Built for the EU AI Act
- Self-hosted models for sensitive data
1,284 runs today
Formnew customer
AI agentclassifiespriority: high
CRMnew lead created
Slack#sales notified
Invoicedraft created
✓alert sent to #sales0.3 s
✓lead from form added to CRM1.4 s
✓email classified as support0.9 s
We build and run systems for
What we build
Down-to-earth AI: the architecture that ties language models to your core systems, so it works in everyday use.
Copilots
Tools that help your people write, code and analyse faster.
Knowledge search with RAG
Your documents and databases, available through plain language.
AI agents
Agents that look things up in your systems and prepare actions for approval.
Chatbots
Connected to CRM, ERP and helpdesk, and able to tell when a human needs to take over.
Data foundation
We collect and clean your data and turn it into vectors, so the answers are precise.
EU AI Act
Traceability, logging and a human in the loop, built in from day one.
Specialist areas
- Python · ML
Python and machine learning
Machine learning that goes from notebook to production, with monitoring and local models where data must stay with you.
Where does AI pay off fastest?
The tasks are repetitiveand take hours every week.
The answers are in your own documentsbut hard to find.
Customer service gets the same questionsover and over.
Invoices are checked by handline by line against the orders.
Search that understands what customers mean
With vectors and hybrid search, the online shop finds the right products even when customers use different words from the product description.
From sandbox to production
- low-risk tasks
Technical assessment
We assess data quality and infrastructure and find tasks with low risk and high value.
- closed environment
Prototype
A working prototype in a closed environment shows whether the technology solves the problem.
- data leak testing
Security testing
We stress-test the system for vulnerabilities and data leaks before it goes live.
- monitoring and maintenance plan
Go-live
Rollout with monitoring, training and a clear model for maintenance.
Three places to start
- When you want to see the value first
Focused prototype
An MVP on one specific task, so you see the effect before you scale.
- Low risk, high value
- Closed environment
- Clear recommendation afterwards
- When knowledge is scattered
RAG solution
Search and answers across your own documents and databases, with sources.
- Access control that mirrors your organisation
- Traceability for audits
- Self-hosted model when needed
- When tasks should be done for you
AI agent
Agents that carry out multi-step tasks and present decisions for approval.
- Connected to ERP, CRM and email
- A human in the loop
- Monitoring in production
A simple chatbot on your own documents can start at a few tens of thousands of kroner. Fully integrated systems cost more, and do more.
Frequently asked questions
What's the difference between copilots, RAG and AI agents?
Copilots help your people work faster while a human stays in control. RAG makes your own data available through plain language. AI agents act on their own, for example by looking things up in the ERP and preparing cases for approval.
What is RAG, and why does it matter?
RAG stands for Retrieval-Augmented Generation. The AI bases its answers on facts from your own organisation instead of guessing. We pull data from sources like SharePoint or SQL, clean it and turn it into vectors.
How do you comply with the EU AI Act?
With traceability back to the source documents, logging of every interaction for audits, and a human in the loop for critical decisions.
What about security and access control?
The system mirrors the access rights in your organisation. An employee should never get answers based on documents they aren't allowed to read.
What does an AI chatbot for businesses cost?
A simple chatbot based on your documents can start at a few tens of thousands of kroner. One connected to CRM, ERP and other systems costs more. We recommend starting with a focused MVP.
What's the difference between a chatbot and an AI agent?
A chatbot answers questions. An AI agent takes actions: it looks things up in systems, sends email and prepares decisions for approval.
How can small and medium-sized businesses use AI?
Start with concrete problems, like invoice handling, a knowledge base for employees or a chatbot that takes load off customer service. Repetitive, rule-based tasks pay off fastest.
Tell us which task takes too long
Describe it briefly, and we'll tell you whether AI is the right tool for it.