Automation · AI · ERP

Business automation and AI adoption

We bring order to operations: records move from spreadsheets into a system with roles and history, AI assistants join the team, and a custom ERP grows around your processes — all on infrastructure you control.

data flow schemathis is how we build it
sources
1C
Email
Spreadsheets
Stock
CRM
Bank
integration layer
what people get
Single source of record
roles, statuses, history
Reports
refresh themselves
AI assistant
plain question — answer from data
01Sound familiar?

When the business grows faster than its records

Automation is not about fashion — it is about the moment manual records start costing money.

Spreadsheet chaos

Excel and Google Sheets: everyone has their own version, edits get lost, and “who changed this” is an eternal mystery.

Reports by hand

Every week someone spends half a day pulling numbers from five sources — outdated by the time the meeting starts.

Processes in people's heads

How to get approvals, who is responsible, where the documents are — two irreplaceable people know. Their vacation stops the work.

Decisions by gut feeling

The owner has no live picture in numbers — only verbal reports. Problems surface when they are already expensive.

02What we do

From process audit to your own ERP

We do not sell a box. We study how your business actually works and build exactly the system it needs.

01
Process audit & mapping

We trace how requests, money and documents actually move. You get a process map and an automation plan with priorities.

02
Process automation

Records and approvals move from spreadsheets and chats into a system: roles and permissions, statuses, reminders, full change history.

03
AI adoption

Assistants working on your company's data: executive summaries, document processing, answers to your team's questions.

04
Custom ERP

A management system built for your company: only the modules you need, your terms and your processes — no paying for “everything at once”.

05
Integrations

We connect what already works: 1C, Google Workspace, Telegram, payment services — via API, with no double entry.

06
Infrastructure & support

Deployed on your server or cloud: monitoring, backups, alerts. The system lives on — and someone is accountable for it.

03Living proof

We run our own business on this platform

Our best case is PMEG's own ecosystem: we manage real construction projects on these tools every day. Below are working products, not mockups.

Executive dashboard

The whole project on one screen: budget, earned value, forecast, critical path. Opens on any device.

Field data system

A replacement for working spreadsheets: role-based data entry, month locking, and a log showing who changed what and when.

AI analyst

Answers questions about project data and prepares executive briefings: what is late, where the budget goes, what needs a decision.

Control center

The whole infrastructure on one screen: services, databases, backups, disk. Problems are visible before anyone reports them.

04what it looks like

Four screens from an ordinary working day

Not mockups and not screenshots: these interfaces are built the same way we build them for clients. The data is illustrative.

sample data
New5
Equipment replacement, shop 2
Customer return
Request #1284
In progress7
Packaging delivery
Forklift repair
Done41
Supplier agreement
05before / after

One request going through approval

The same process before and after. Switch and compare.

Eight steps and no trace

Every step lives in its own channel, and nobody sees the whole picture.

  1. 01An employee posts the request in a chat
  2. 02The manager says "fine" out loud in a meeting
  3. 03Accounting asks for a copy by email
  4. 04The file is edited in two copies at once
  5. 05The finance director is away — everyone waits
  6. 06Nobody remembers who approved it
  7. 07The payment goes out late
  8. 08A month later someone hunts for where it got lost
The timeline is luck. The owner is whoever agrees to be.
06scenarios

What this looks like across industries

These are typical scenarios rather than named client stories: they show how the problem looks and how it gets solved.

A retail floor after closing, shelving rows in warm light
typical scenario

Retail chain

before

Nine stores, each with its own stock spreadsheet. The summary was compiled by hand on Mondays and was stale by Wednesday.

what we did

Unified stock and sales accounting, automatic purchase requests at minimum levels, a live report for the owner.

after

Stockouts stopped being a discovery. Orders are generated by the system, not by someone's memory.

Summary: from two days to seconds
A warehouse aisle, tall racking with pallets in warm light
typical scenario

Logistics

before

Requests arrived by email, chat and phone. Only the dispatcher handling a run knew its status.

what we did

A single request desk with statuses and owners, integration with 1C and Telegram, full change history per request.

after

Anyone can see where the cargo is and who is responsible. A dispatcher's holiday no longer stops the work.

Lost requests: none
A production line with a conveyor under warm work lights
typical scenario

Manufacturing

before

The output plan lived in Excel, the actuals in the foreman's logbook. Discrepancies surfaced at month end.

what we did

Output recorded per shift, material consumption norms, automatic batch cost calculation.

after

Overconsumption is visible the same day, not in a report a month later.

Batch cost known on the day of production
A service company office in the evening, reception desks and glass partitions
typical scenario

Services

before

Contracts sat in folders and renewal dates in the lawyer's head. Approvals went by email and left no trace.

what we did

A contract register with statuses and reminders, approval routes, access rights and complete history.

after

Not a single missed renewal. It is visible who holds a document and for how many days.

Approval: from 11 days to 4
07builder

Assemble your own solution

Tick what hurts. We will show the make-up of the system and the time to a working prototype.

what hurts today
what we would build

Tick at least one item on the left and we will assemble the scope and the timeline.

08How we work

A working prototype first, the big system second

We do not start with a hundred-page spec. You decide on the big system while looking at a working screen with your own data.

01
Audit

We study how processes and records work today and where time and money leak.

1–2 weeks
02
Prototype

A working system on your real data — something to touch, not a slide deck.

2–4 weeks
03
Rollout

We turn it into a product: permissions, integrations, team training. Launched in stages, without stopping the business.

from 1 month
04
Support

Monitoring, backups, new features as you grow. The system grows with the business.

ongoing
09Why PMEG

Automation by people who live on it

Proven on ourselves

We do not resell someone else's platform: we run our own construction projects on the system we built.

Engineering discipline

We come from projects where a mistake costs billions. The same standard goes into every implementation.

Your data stays yours

The system runs on your server or your cloud. Access, audit log and backups are under your control.

Modern stack

The technologies global companies build products with — no legacy platforms, no perpetual licenses.

10FAQ

Frequently asked questions

How is this different from an off-the-shelf CRM or 1C?

An off-the-shelf system makes the business adapt to it. We do the opposite: the system mirrors your processes and your vocabulary, has no unnecessary modules — and you do not pay for what you do not use.

Everything we have is in Excel. Is that bad?

Up to a certain size it is fine. It becomes bad when spreadsheets start costing money: lost edits, double entry, manual reports. We migrate data carefully and usually run the system in parallel with the sheets until the team settles in.

How much does it cost?

It depends on scope, which is why we start with an audit and a prototype: a limited budget and a tangible result, after which the cost of the full system can be estimated precisely.

What about confidentiality with AI?

The assistant only works with the data you grant it, on infrastructure under your control. What is shared and where is fixed in writing before we start.

Who maintains the system afterwards?

We do: support is part of the service, from monitoring and backups to new features. The code and documentation are yours — we can hand the system over to your team if you wish.

Let us show it on your case

Tell us which process eats the most time — we will propose how to automate it and show something similar in production.

Discuss your case
08Contact

Ready to take your project under control?

Tell us about the task — within 1–2 days we will prepare a team structure, a roadmap and a commercial proposal.

Send an enquiry

Describe the task — we will come back with a team structure and an initial estimate.