AI agents that do the work, not just answer in a chat.
An agent differs from a chatbot in that it has access to your systems and permission to act: find, calculate, file, hand over. We design such agents around a specific process — with explicit authority boundaries, logs and cost control.
Break the process into steps
First we map what a person actually does by hand and where time is lost. The agent is built for that route, not for “AI in general”.
Tools and system access
The agent works through tools: CRM, knowledge base, mail, payments, internal services. Each tool is an explicit contract, not blanket access to everything.
Authority limits and a human in the loop
What the agent does alone, what it sends for approval and what it never touches is decided up front and lives in code, not in a prompt.
Observability and cost
Step-level logs, quality evaluation on your scenarios, token-cost monitoring. You can see what the agent did and what it cost.
How is an AI agent different from a chatbot?
A chatbot replies with text. An agent performs steps in your systems: it finds the data, calls the right tools and takes the task to a result, not to a reply.
What if the agent does the wrong thing?
That's why authority limits live in code: irreversible actions go through human approval, everything else is logged step by step and can be traced.
Do we need an agent or is plain automation enough?
If the steps are fixed, ordinary automation is cheaper. An agent pays off where judgement is needed: parsing an unstructured request, choosing a route, gathering data from several places.
Which models does it run on?
Chosen for the task and data constraints: external LLM providers or self-hosted models, weighing privacy and cost.
What does it cost to run?
Cost comes from request volume and context length. We estimate it before the start and build in limits and monitoring so spend is never a surprise.
AI agent platforms in 2026: what a business should choose
Eleven platforms, what each of them charges for, where its ceiling is and what actually works from Russia. Every figure comes from the vendor's own public page, checked on 6 September 2026, with the source named. No rankings and no top-ten lists: the choice depends on what you are building, not on a position in a table.
How to build an AI agent: what you need beyond the prompt
The prompt and the model are the smaller part of the job. An agent becomes usable when it has tools, explicit authority boundaries, state, a log and cost control. A step-by-step breakdown of what it is made of, how to get it to production and where it breaks.
Checklist: are your documents ready for RAG
PDF, 2 pages. No sign-up, no email — just the file.