Public chatbots are not right for sensitive work
Customer data, offers, and internal information need better control than copy-paste into an external tool.
OEJ builds AI agents that fit into your company’s real workflows. We start with one clear place, such as Gmail, Calendar, or Drive work through Telegram, and expand the agent when the value is visible.
A public chatbot can help write text, but it does not safely solve customer requests, document summaries, or internal follow-ups on its own. For that, AI needs to fit the workflow and access must be explicit.
Customer data, offers, and internal information need better control than copy-paste into an external tool.
An agent should help with actual tasks: find information, prepare drafts, summarize material, and queue next actions.
Before building, we define where data moves, which permissions the agent has, and what it is not allowed to do.
The point is to avoid company knowledge and customer data moving uncontrolled through third-party services.
Processing and storage are designed to stay inside the European Union where the chosen integrations allow it.
The agent receives only the permissions needed for the selected workflow.
You should be able to see what the agent did, when, and based on which input.
Example customer-request agent: AI prepares the work, but the important decision stays with a person.
A customer writes through email, a form, or a website channel. The agent receives only the context needed for that workflow.
The agent summarizes the request, finds relevant context, and prepares a reply or next action.
A company owner or employee reviews the result, edits if needed, and sends or starts the action themselves.
OEJ builds AI agents that connect to a company’s tools and agreed workflows. An agent can help sort emails, summarize documents, prepare reply drafts, queue follow-ups, or find internal information.
The first step does not need to be a big project. We choose one repeated job where an AI agent can show value quickly and where the boundaries are easy to agree.
Often the easiest first step is a Google Workspace and Telegram workflow, because the company does not need to adopt a complicated new tool.
We define what the agent may read, where it may create drafts, and which actions require human approval.
If the first workflow genuinely saves time, the same solution can be expanded calmly from there. If not, that is also a useful answer.
OEJ OÜ is a one-person company based in Tallinn. The goal is to make self-hosted AI agents understandable and useful for local businesses.
If you have one repetitive process where assistance would save time or reduce data risk, it is a good pilot candidate.
A good start is a short description of one task that takes too much time or too often gets stuck. I’ll reply whether it could become a sensible first AI-agent workflow.