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Home/AI agents/Implementation
AI agents · Implementation

An AI agent is part of the process, not a standalone toy

We build the agent into a business process: task and data first, then integration, and finally a measurable result. A single-channel, single-task agent typically goes live in 2–4 weeks.

6 stepsWith KPIsAfter testingMonitoring
Stages

Six steps: from task to monitoring

Timelines are for a single-channel, single-task agent. Agents that connect to several systems are built in stages.

01Task and KPI2–5 days

Which work to hand to the agent, how long it takes now and how the result will be measured. Baseline KPIs come from the CRM and reports.

02Data preparation3–7 days

The catalogue, FAQs, scripts and SOPs are gathered and cleaned up. Outdated and conflicting documents are removed, and every source gets an owner.

03Scenario and guardrails2–4 days

What the agent does, when it hands off to an employee and what it never does are written down and approved.

04Integration3–10 days

The channel (Telegram, Instagram, website), CRM, ERP and calendar are connected via API. A separate technical user is created for the agent.

05Testing3–7 days

First on a test set, then with employees, then on a share of real customers. Errors are fixed along the way.

06MonitoringOngoing

Weekly reviews in the first month: KPIs, error samples, unanswered questions. Monthly reports after that.

Results

What you get at each stage

Every document stays with you, so another team can support the agent later.

StageDocument or deliverable
Task and KPIAgent profile: task, boundaries, KPIs and baseline values
Data preparationA cleaned-up knowledge base and a list of source owners
Scenario and guardrailsScenario, handoff rules, list of off-limits topics
IntegrationIntegration diagram, permissions table, data flow map
TestingTest set, results report, list of fixes
MonitoringKPI report, staff guide, 30 days of support
KPIs

Three groups of metrics for each agent

Specific targets are agreed during the diagnostic, based on the baseline.

Speed

  • First response time
  • Task completion time
  • Response time after handoff to an employee

Quality

  • Wrong answer rate (weekly sample)
  • Results accepted without edits
  • Complaints from customers or employees

Workload and results

  • Handoff rate
  • Tasks the agent closed on its own
  • Business metric: deals, bookings, processed documents
Roles

Who does what in the project

The agent’s owner must be on the client side.

Client: agent owner

Updates the knowledge base, reviews handed-off conversations, tracks KPIs.

Client: department staff

Take part in testing, flag wrong answers, handle the tasks handed off to them.

BUline

Architecture, integration, scenario, testing, staff guide and first-month monitoring.

Getting started

Which task to start with

For the first agent, we pick a repetitive, measurable, low-risk task, such as frequently asked questions on Telegram or creating drafts from documents. Once the results are visible, we move on to the next agent. The most widely used agents are the sales assistant, the booking agent and the knowledge base.

  • Repeats dozens of times a day
  • The result can be measured in numbers
  • Errors cause little harm and are quick to fix
  • The required data already exists
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No CRM or ERP yet?

The data the agent collects has to land in a system. It is usually faster to set up amoCRM, Odoo or MoySklad first and then connect the agent.

FAQ

Frequently asked questions

Does the agent reply to customers during testing?

Not at first: it works on an internal test set and with employees. Then it is switched on for part of the real traffic, for example only outside business hours.

Can we change the agent ourselves after launch?

Yes. Your employee updates the knowledge base and reply templates. We provide a guide for changing the scenario and integrations.

Can we build several agents at once?

You can, but we don’t recommend it. The first agent establishes how data, permissions and monitoring are handled. The next agents are built on that foundation faster and with fewer errors.

What happens during the diagnostic?

We review your processes, channels and systems, rank the tasks that could be handed to AI by benefit and risk, and propose a task, KPIs and a plan for the first agent.

What if the agent doesn’t deliver the expected results?

If KPIs fall short of the agreed level during testing, we analyze why: the data, the scenario or the choice of task. Sometimes the right conclusion is not to hand this task to AI yet.

Free diagnostic

We identify which work can be handed to AI

We review your processes and recommend a specific task, KPI and plan for your first agent.