AI integration
We connect a language model to your backend: request triage, data extraction from documents, search by meaning instead of by keyword.
New direction
Artificial Intelligence for Business
Not a neural network for its own sake, but a concrete task: cut manual work, take load off support, find an answer inside your own documents. We start from what you already have and measure the time it saves.
Five directions
AI assistants and chatbots
An assistant that answers from your knowledge base and admits when the answer is not there, handing the conversation to a person with its history.
AI process automation
The routine done by hand today: request classification, document completeness checks, report and export preparation.
AI agents
An agent does the work instead of answering questions: it triages email, keeps CRM records, tracks tasks and deadlines. Actions stay under your control.
Company knowledge base
A second brain for the business: procedures, contracts and correspondence in one store, with search and answers from your data rather than from the internet.
Which one fits your task
The five directions solve different problems, and confusing them is expensive. Here is how they differ in practice.
| Direction | When this is your case |
|---|---|
| AI integration | The product already works and now has a task rules cannot solve: parse a text, extract data from a document, find something by meaning. |
| Chatbots and assistants | You need a conversation with a customer or an employee: answers from your own materials, with handover to a person. |
| Process automation | There is a repeatable process with manual steps: classification, document checks, report preparation. |
| AI agents | You need an action rather than an answer: create a record, set a deadline, triage email. The agent works inside your systems. |
| Company knowledge base | Knowledge is scattered across drives and chats, search finds nothing, and a new hire takes months to become useful. |
Our own practice
How we use AI ourselves
We keep a knowledge base across twelve projects: shared memory, work logs and written procedures the team uses every day. This website was designed and written inside it. We do not retell other people's articles about AI; we show what we use ourselves.
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One document store across twelve projects instead of messenger threads
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Work logs and written procedures instead of verbal agreements
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Answers from internal company documents rather than from the internet
We show the structure and the result. Note contents, client names and credentials are never published.
Have an idea for a new product, or need to grow an existing one?
Tell us about the task. We will study it and propose an option that makes sense technically and economically.
We reply within one business day · Telegram @sbunyod