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SAMSA.AGENCY
RUUZEN
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RUUZEN
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Automation

AI automation, assistants and internal agents

Industrial robotic arm automating a workflow

We automate lead processing, responses, qualification, routing and internal processes — no AI for the sake of AI.

For sales, support and operations teams with too many manual touchpoints and slow customer response.

Discuss AI automation

Direct answer

AI Automation

AI automation at SAMSA.AGENCY means adding focused AI workflows to real operations: lead qualification, customer replies, routing, CRM updates, internal assistants and knowledge workflows. We design fallbacks, logs and quality control so automation helps instead of creating operational risk.

Price range
Guide: Telegram bot from UZS 2,250,000, knowledge-based AI pilot from UZS 5,400,000, CRM integration from UZS 9,000,000.
Timeline
A pilot usually takes 2–3 weeks. Multi-system integrations usually take 4–8 weeks.
Not for
Not a fit without a clear scenario, a process owner and a metric for judging AI value.
Automation server with physical review and approval modules

Control

Automation with clear boundaries

AI handles repeatable work while critical decisions remain reviewable. Logs, roles, limits and human approval are designed into the workflow before launch.

Regional rates

Pricing for Uzbekistan, Russia and Belarus

Tashkent and regions

Uzbekistan

Telegram bot

from UZS 2,250,000

Moscow and regions

Russia

Telegram bot

from 45,000 ₽

Minsk and regions

Belarus

Telegram bot

from 1,350 BYN

The exact price is fixed after a short brief. Taxes, platform fees, third-party services and media spend are not included.

Use cases

01
  • Lead qualification
  • Sales assistants
  • Support copilot
  • Internal knowledge workflows

Deliverables

02
  • Scenarios
  • LLM orchestration
  • CRM integrations
  • Logs & fallback chains
  • Secure server delivery

Proof points

03
  • Business scenario first, then model
  • Error control and fallback
  • Integration into real team processes

How we make decisions

We introduce AI into a specific process with a known input, output and human handoff. Before building, we estimate repetitive volume, error cost, data availability and the integrations required for real work.

Bounded role

The agent gets defined actions and sources. Low-confidence situations pass to a person with full context.

Integrations

CRM, Telegram, knowledge sources and internal APIs become one workflow instead of disconnected chats.

Quality control

Logs, test scenarios, permissions and human approval for critical actions are designed before launch.

Process

  1. 01

    Diagnosis

    We define the business problem, current constraints, available data and the success criterion before estimating delivery.

  2. 02

    Solution design

    We map the solution, integration points and launch sequence so risks and dependencies are visible before expensive implementation.

  3. 03

    Production

    Delivery moves in short, reviewable iterations. Every stage produces a concrete artifact for approval, not a report about activity.

  4. 04

    Launch and growth

    We verify analytics, forms and real workflows. After launch, improvements enter a backlog ranked by leads, revenue or time saved.

Before delivery starts, we record the baseline and keep metrics from different funnel stages separate. More impressions, clicks or conversations do not automatically mean a business outcome. Every solution therefore has one leading metric, guardrails and a review date, while access, documentation and operating ownership are transferred to the client team.

What must be ready

  • A business owner can prioritize work and accept the outcome instead of approving isolated screens, ads or pieces of copy.
  • The current baseline, data source and comparison period are known. If analytics is missing, instrumentation becomes the first explicit stage.
  • Materials, domains, ad accounts, CRM access or APIs required to test the complete journey are available to the delivery team.
  • Legal, brand and technical constraints are documented, including personal data, access roles, approval steps, infrastructure and permitted vendors.
  • The team agrees on the minimum launch outcome and deliberately leaves unproven ideas in the backlog until real usage data exists.

How we evaluate the result

  • Technical quality is reviewed separately through availability, speed, event accuracy, error handling, integrations and data transfer between systems.
  • Behavior is measured by the user’s next meaningful action rather than generic time on page or raw page-view volume.
  • Commercial impact connects lead quality, stage conversion, processing cost and the final CRM, order or support outcome.
  • Changes are compared across equivalent periods and segments; seasonality, budget shifts and parallel campaigns are marked as separate variables.
  • The next backlog follows the review: risk fixes come first, then growth hypotheses with a test cost and an expected signal.

FAQ

Can we start with one scenario?

Yes, it is best to launch AI as a narrow pilot with a specific metric.

Do you work with Telegram and CRM?

Yes, including lead forms, routing and internal panels.

Which models do you use?

We pick the model for the task: OpenAI, Anthropic, local models or a hybrid if cost, speed or privacy matters.

DISCUSS
PROJECT

Tell us what you want to build or improve. We will reply within one business day and discuss the next step.