AI that makes real sense for your business
We design and integrate AI where it can save time, cut costs or make company data easier to reach.
We build assistants, automations, document processing and search across your own data. We start with a specific problem and look for a solution that pays off.
What we do with AI
These are the areas where AI most often helps companies today.
AI chatbots and assistants
Assistants that work with your content and data. They help customers on your website and your internal teams.
Process automation
AI handles emails, orders, tickets and other repetitive tasks that eat up time today.
Document processing
We extract structured data from invoices, contracts and forms, with no manual retyping.
Search across company data
RAG solutions that find answers in your documents and knowledge, not at random on the internet.
AI in websites and online shops
AI can help with recommendations, customer support and generating or localising content. We use it where it improves a specific part of the product.
What's included
We handle an AI project as a whole, from checking whether AI makes sense at all to operation and continuous improvement.
Problem and use-case analysis
First we check whether AI makes sense at all and what it could deliver.
Choosing the right model
Based on the task, the data, security requirements and budget.
Integration into your systems
Connecting it to websites, internal systems and existing processes.
Secure connection to your data
We also set up how sensitive content is handled.
Pilot on real data
We test the solution on your own cases before any wider rollout.
Operation and quality measurement
After launch, we monitor quality, costs and usage, and keep fine-tuning the solution.
Who we build AI solutions for
For mid-sized and large companies with a specific problem that is worth solving with AI.
You don't need an AI project ready to go. A problem you want to solve better is enough.
Typical signs
Lots of repetitive tasks
The same steps are done every day, by hand, in several places at once.
Support answers the same questions
That leaves less time for the complex cases that really need a person.
Large volumes of documents
Invoices, contracts and forms that someone retypes by hand.
Data people struggle to get to
The information exists, but finding an answer takes a long time and depends on one particular person.
If AI isn't the right route, we'll tell you.
Your data stays yours
When a solution works with company data, the model doesn't need to know everything. For each question it receives only the relevant context from your documents and systems.
Documents and data
contracts, invoices, internal knowledge, website content
Index of your data
content can be searched by meaning, not just by keywords
Language model
chosen to suit the task, the data and security
Answer from your data
an assistant on your website, in an app or in an internal tool
Depending on how sensitive the data is, we work through a secured API or choose a model that runs in your own or another controlled environment. We decide this at the design stage, not after deployment.
How an AI solution comes together
We move from the problem to a pilot, and only then to full deployment. That way you decide on a larger investment based on proven results.
We analyse the problem
We look at the process, the data and the expected benefit. Together we check whether AI is the right tool.
We validate the solution
We build a pilot or PoC on real data. We quickly find out what works and where the limits are.
We put it into practice
We connect the solution to your systems, website or internal processes, so it becomes part of a working product.
We run and improve it
After launch, we monitor quality, costs and usage. Based on the results, we keep fine-tuning the solution.
The problem picks the technology
We work with OpenAI and Anthropic (Claude) models, and with open-source models where needed.
We use RAG, vector databases, API integrations and technologies that fit into your existing stack.
The model isn't the goal. It's a tool.
We choose the model to suit the specific task, the data, security and budget.
What AI solutions are built on
AI is the top layer. Underneath it, the data, integrations and search have to work. The projects below are not AI projects. They show the work with systems and data that an AI solution rests on.
Why trust Webikon with AI
AI as part of a working product
We don't hand over AI as a standalone demo. We connect it to the website, app, company systems or process where it is meant to deliver results.
We start with the problem, not the technology
First we look for a specific use case and what it would bring. Only then do we talk about the model and the architecture.
A partner after launch, too
For us, a project doesn't end at launch. We provide operation, support and further development based on what the solution shows in practice.
Experience in development, not just AI
Our AI solutions build on more than 16 years of experience developing websites, apps and digital products. We also understand the systems AI needs to plug into.
We deal with data from the start
At the design stage, we work out what data the AI needs, where it goes and how to protect it.
Common questions about AI solutions
If you can't find the answer here, write to us. We'll be glad to help.
What can AI realistically do for a company today?
It delivers the most where the same tasks repeat or where people work with large amounts of information. Typically that means customer support, document processing, search across company data or process automation. We recommend starting with one specific use case with a measurable benefit.
How much does an AI solution cost?
It depends on the problem, the scope of integration, the data and the operational requirements. For larger solutions we recommend starting with a pilot that tests the benefit and the technical options before a bigger investment.
Where does our data go and how is it protected?
It depends on how sensitive the data is and what the project requires. We can work through a secured API or choose a model that runs in your own or another controlled environment. We settle how the data is handled at the design stage, not after deployment.
Which models do you build on?
We use OpenAI, Anthropic (Claude) and open-source models. We choose the specific model based on the task, output quality, data requirements, security and cost.
Can we start small?
Yes. With AI it's often wiser to start with a pilot than with a large project. On real data we test the benefit, the quality and the limits of the solution. If it proves itself, we scale it up.
Tell us the problem.
AI comes second.
You don't need a finished solution. Tell us what takes up too much time in your company today or where data gets lost. Together we'll work out whether AI makes sense in your case and where to start.
No-obligation consultation.
We reply within 24 hours.