Working with companies in Kazakhstan and remotely.

documents · policies · reconciliation · reports

AI agents take routine work off your hands

Not another system where tasks still have to be moved by hand. We measure how many hours a month a specific task takes today, put an agent in place to do that work, and repeat the measurement after launch.

Measure hours before the start
Agent does the work
Review the person decides
Report hours after launch

Five tasks an agent can handle.

Incoming document intake

Invoices, delivery notes and acts arrive by email and messengers, then get keyed into the accounting system by hand. The agent reads the incoming document, extracts details, amounts and numbers, and prepares an entry for review.

  • scans, PDFs and phone photos
  • extraction of details and amounts
  • matching against contract and request
  • approval queue

Answers from internal policies

A manager answers the same questions in chat over and over: how to file it, where to send it, who signs it. The agent answers from your own documents and shows which clause the answer came from.

  • search across policies and instructions
  • answer with a link to the source
  • role-based document access
  • unanswered questions surface to the owner

Request checks before approval

The approver manually checks whether everything is attached and whether the amount stays within the limit. The agent checks completeness and rules before the request takes anyone else's time.

  • attachment completeness
  • limits, budgets and rules
  • draft comment for the approver
  • reason for returning it to the requester

Data reconciliation across systems

Exports from 1C, the bank, inventory and CRM are merged in Excel by hand, and discrepancies are hunted by eye. The agent reconciles the sources on a schedule and surfaces only what does not match.

  • scheduled reconciliation
  • discrepancy list with amounts
  • history for each case
  • notification to the owner

Recurring reports

The monthly report is assembled by hand from several sources, and the "what changed" commentary takes another day. The agent assembles the report on a schedule and writes which numbers moved and why.

  • collection from several sources
  • finished file on a schedule
  • commentary on the changes
  • delivery to recipients

Measure, test, then launch.

01

Measurement

We count what the task costs today: who does it, how many times a month it repeats, how many minutes one item takes.

02

Decision limits

We fix what the agent decides on its own, where human review is mandatory, and what it never does.

03

Prototype

We build the agent on your real documents and questions, show the answers and go through the mistakes together.

04

Development

We connect sources, role permissions, the review queue, the action log and exchanges with your systems.

05

Working in pair

For a while the agent runs alongside the person: we compare results and raise its autonomy step by step.

06

Launch and re-measurement

We hand over access and instructions, repeat the measurement on the same process and record the difference in hours.

The agent, review tools and handover.

Measurement and rules

Task map, frequency, time per item, the agent's decision limits and the mandatory human checkpoints.

Model and logic

Model selection for the task, the field extraction schema, validation rules and a run on your real examples.

Sources and access

Connecting email, file storage, accounting systems and knowledge bases with role-based permissions.

Review interface

Approval queue, link to the source of each answer, result editing and a reason for rejection.

Integrations

Exchange with 1C, Bitrix24, SAP, iiko, Directum, CRM, websites and other systems through available APIs and standard mechanisms.

Handover and log

Source code, access, instructions, the agent's action log and the repeat hours report after launch.

Before we estimate your first agent.

First stage

We take one task, measure it in hours and define what the agent does on its own and what goes to a person for review.

What affects cost and duration

The format and quality of source documents, the number of sources and rules, integration depth, access requirements and the acceptable error rate.

What we need for an estimate

Real examples of documents or questions, the current policy, a list of systems and a person who will check the agent's answers.

Result and fit

You receive a working agent, access roles, an action log and a repeat measurement of the hours. This format fits one recurring task; a company-wide scope should start from Mini ERP or ERP.

Questions about AI agents.

How is an AI agent different from a process automation system?

A system shows which stage a task is at and who owns it, but a person still does the work. An agent does the work itself: reads the document, extracts fields, reconciles data, drafts an answer or a report. A person reviews and approves the result.

How are the saved hours measured?

Before the start we measure the task: who does it, how many times a month it repeats and how many minutes one item takes. After launch we repeat the same measurement on the same process. The difference is the result, and it appears in a report rather than in a promise.

What happens if the agent gets something wrong?

The agent never acts silently: its result goes into a review queue with a link to the source it used. Role-based permissions, an action log and mandatory human approval on irreversible steps. Autonomy is raised only after the agent has been checked on real work.

Which systems does the agent work with?

1C, Bitrix24, SAP, iiko, Directum, CRM, email, file storage, websites and other systems can be connected in the agreed scope through available APIs and standard exchange mechanisms.

Start with
your task.

20–30 minutesFree

  • Review your process
  • Define the first stage and next step
What to bring to the call

Tell us who does it, how many times a month it repeats, how long one item takes and which systems hold the data.

Discuss your task Describe your task on WhatsApp or arrange a call.