AI chatbot for businesses
We build website and message chatbots that use your approved sources, ask follow-up questions, qualify requests, and leave a clean trace for the team. The goal is not to replace every conversation, but to remove repetition and prepare a better next step.
Book a discovery callA chatbot should have a clear task, approved sources, and a rule for when to stop. That is why we build the pilot around a small number of controlled scenarios.
Detects intent
Separates a question, sales request, support issue, status check, complaint, or handoff request.
Asks for details
Does not jump to an answer if contact, code, topic, deadline, or another important detail is missing.
Checks knowledge
Answers from approved sources or clearly marks when there is not enough information.
Text demo
The example is from an online store: the customer asks about a specific product, the chatbot checks approved catalog data, and collects the details sales needs for an offer.
Chat example
Customer
Do you have the ErgoFlex Pro office chair in black? I need it for a home office.
AI chatbot
According to the catalog, ErgoFlex Pro is available in black and has an adjustable backrest, lumbar support, and a declared load rating up to 120 kg. To check availability, please send the quantity and delivery city.
Rule: answer only from the approved catalog and ask for offer details
Customer
I need one chair for Novi Sad. If possible, send me an offer by email.
AI chatbot
I noted the request: ErgoFlex Pro, black, 1 unit, delivery to Novi Sad, offer by email. Please send the email address and the system will automatically check stock and price, then send the offer.
Action: the chatbot checks catalog/ERP data and automatically sends the offer
The best first chatbot is not the broadest one. It is useful where questions repeat, the team loses time, and conversations are not recorded cleanly.
Pricing, timelines, terms, statuses, documents, and basic information repeat across the website, messages, and email.
Sales receives vague messages and later has to ask for details that could have been collected immediately.
Answers exist in documents, catalogs, price lists, or previous conversations, but the team searches manually.
When the chatbot does not know the answer, it should hand off with context instead of making the user start over.
We start with the channel where customers already ask questions, then connect the knowledge and system where the team wants the result.
Website, WhatsApp, Viber, Instagram/Meta, and email, depending on where you already receive the most requests.
FAQ, documents, catalog, price list, procedures, website pages, and previous answers approved by the team.
Conversation summary, CRM lead, support ticket, team email, or task in an internal tool.
A chatbot should have a clear task, approved sources, and a rule for when to stop. That is why we build the pilot around a small number of controlled scenarios.
Separates a question, sales request, support issue, status check, complaint, or handoff request.
Does not jump to an answer if contact, code, topic, deadline, or another important detail is missing.
Answers from approved sources or clearly marks when there is not enough information.
Prepares a summary, lead, ticket, or task instead of leaving the conversation only in the chat window.
When judgment, negotiation, or a sensitive answer is required, the team gets context and can continue.
Answers from approved knowledge with clear limits and handoff when there is no safe answer.
Collects details and sends sales a summary that can be handled immediately.
Creates or enriches a record when the action is approved and technically supported.
Usually the website or message channel where repeated questions already appear.
Select the documents, FAQ, and rules the chatbot may use.
Decide when the agent stops, what it records, and who receives the conversation.
Track how many requests were answered, how many were qualified, and where improvement is needed.
The chatbot does not need to invent. It uses knowledge the company approves.
When the answer is not safe, the conversation goes to a person with a summary.
CRM, tickets, or email are used only through permitted rules.
Yes, if we prepare the documents as approved sources and define what the chatbot may use in the answer.
Yes. It is most useful when it sends a structured summary, contact details, and topic instead of a raw conversation dump.
The chatbot can return the conversation to the allowed topic, ask for more information, or hand off to a person.
Yes. It is useful to prove the scenario on one channel first, then expand it to other channels.
Send us your 10 most common questions and where a qualified request should end up. We will suggest the first pilot scenario.
Tell us about your workflow and goals. We respond within 1 business day with clear next steps.
Based in Serbia, working worldwide.
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