Defining the task and the sources
We decide which questions the chatbot should handle, which information it may use and in which situations the conversation should be handed to a person.
AI chatbots and customer service
An AI chatbot can answer customers' questions, help them choose a product or service and find information in your company's knowledge sources. We build chatbots that work with your content and systems, hold conversations in Latvian and hand the conversation to a person when that is needed.
A conversation with your information instead of a script with buttons
A traditional chatbot leads the user through scenarios prepared in advance. An AI chatbot can understand a question asked in the user's own words and look for answers in the sources you specify - product and service descriptions, instructions, frequently asked questions, documents or other systems.
What matters is not only how well the language model holds a conversation, but also where the information comes from and what the chatbot does when there is no reliable answer. We define the sources, the limits of its answers and the conditions for handing a conversation to a person.
What an AI chatbot can do
Answer questions
Uses the information sources you have approved to answer common questions from customers or staff, including outside your team's working hours.
Take pressure off your team
Takes over repeated requests for information, so that your staff can spend more time on the questions that need a person.
Help people choose
Asks clarifying questions, explains the differences and helps people find a suitable product, service or next step, following the conditions you define.
Show where information is missing
Unanswered and unclear questions help you see which topics matter to customers and where the knowledge base or the website content needs adding to.
We'll show you how a chatbot would work with your information
We choose a specific use case and assess which sources, integrations and control mechanisms it needs.
Where a chatbot can be used
- On a website or in an online store, for customer questions, product choice and preparing enquiries
- In messaging channels, where the chosen platform and its integrations support it
- In the customer service process, together with a CRM, order system or other company systems
- Inside the company, as a staff assistant for working with documents, instructions and the knowledge base
How implementation works
Building the knowledge layer
We put the necessary content and data sources, access rights and answer rules in order. Where needed, we connect the chatbot to other systems.
Testing real questions
We check typical and more difficult questions, unclear wording, missing information and situations in which the chatbot should not give an answer.
Launch and improvement
After launch we analyse the quality of conversations, the unanswered questions and the changes needed in the knowledge sources or in the rules the chatbot follows.
Start with one specific task
A good first use case is repeated questions whose answers are already in your company's content or systems. Send us your website address and a short description of what customers ask most often - we will assess what kind of chatbot would be justified for that process.
Frequently asked questions
How much does it cost to build an AI chatbot?
The cost depends on the chatbot's task, the volume of knowledge sources, the integrations required, the channels, the languages and the control requirements. A simple information chatbot and a solution that works with customer or order data are projects of a different scale, so we set the price after assessing the specific use case.
Does an AI chatbot understand Latvian?
Yes, an AI chatbot can be built to hold conversations in Latvian. Before launch we check its answers against the questions, terminology and wording typical of the company concerned.
What does the chatbot do if it doesn't know the answer?
We define what the chatbot does when there is no reliable answer - for example, ask for clarification, say that it does not have enough information, or hand the conversation to a person. Instructions alone cannot guarantee that a language model will never be wrong, so controlled sources, testing and appropriate limits on its answers matter as well.
Can a chatbot be connected to an online store or a CRM?
Yes, if the system concerned has a suitable means of integration, or one can be built. A chatbot can, for example, use product or order information or prepare an enquiry in the CRM. If you need it to carry out multi-step actions in systems on its own as well as hold a conversation, an AI agent may be the better fit.
Can a chatbot also be an internal virtual assistant for staff?
Yes. The same approach works for an internal virtual assistant that helps staff find answers in procedures, product information or internal documents. Access to information is limited according to each employee's role.
Does a chatbot have to say it is AI?
Yes. The EU AI Act requires people to be told that they are interacting with an AI system unless this is obvious. That is why we make the chatbot say so at the start of the conversation. We explain how the Act affects other AI solutions on the AI solutions page.