Taking on new automation work

Chaos in,Systemsout.

runs while you sleep

Secure AI automation — from an engineer with a Check Point cybersecurity background. I turn manual processes into systems that run themselves. Every demo on this site is my own working n8n + OpenAI build: go try it.

or reach me directly:
See the demos

Pick what to automate

AI engine

n8n + LLM

pick an input above
Check Pointcybersecurity background
n8n · OpenAImy working stack
RUI work in Russian

Built on the stack you trust

AI
OpenAIOpenAI
AnthropicAnthropic
Automation
n8nn8n
MakeMake
ZapierZapier
Channels
TelegramTelegram
SlackSlack
DiscordDiscord
Data
SupabaseSupabase
NotionNotion
SheetsSheets
AirtableAirtable
Chaos
Systemsin → out

Your team drowns in busywork while data sits idle

Busywork eats the day

Copy-paste between sheets, manual replies, data shuffling. Hours lost on what a system should do.

AI that misses the point

Everyone talks AI, but it never lands in real processes. Plenty of ideas, zero deployment.

Data in chaos

Numbers scattered across tools. A report takes half a day. Decisions made blind.

What I do

Four ways to hand the grind to machines

Dmitry Parshin
I ship, not pitch
Orbient.pro
About me

Hi, I'm

Dmitry Parshin

AI Integrator & Automation Engineer

I build AI systems that triage requests, answer customers and pull data into one place. Everything I show runs for me first: this site, its demos and lead intake are built on my own n8n and OpenAI setups.

Behind me — an engineering degree in IT and a cybersecurity background at Check Point, one of the world's top companies in the field. I don't build 'just another chatbot' — I engineer reliable, secure systems wired into your processes.

Per McKinsey, at least a third of the tasks in roughly 60% of jobs can be automated. In practice that removes a meaningful chunk of manual hours.

Check Point

cybersecurity at a world-class firm

Engineering degree

majored in IT

Backend + AI

Python · n8n · OpenAI · RAG

Stack:n8nopenaipythonlangchainpostgresqlsupabasedockertypescript
How it works

From chaos to system in four steps

01 · 1–2 days

Audit

I map your processes, find time sinks and where AI pays off.

You get

A process map and a list of automation points

02 · 3–5 days

Prototype

In days I build a working prototype. You see results, not slides.

You get

A working prototype you can actually use

03 · 1–3 weeks

Deploy

I ship to production, integrate your stack, train the team.

You get

A live system, integrations and team onboarding

04 · ongoing

Support

I watch the metrics, tune, and scale as you grow.

You get

Monitoring, tweaks and scaling

Impact, not promises

Dozens of hours

of manual work removed every month

Hours → minutes

that's how routine work shrinks

Replies in seconds

requests handled around the clock, no human on shift

Report in a click

instead of half a day of manual assembly

Free

Free automation audit

In 20 minutes I'll map your processes and show what to automate first. No obligations, no hard sell.

  • Where you lose time and money
  • What to automate first
  • A rough plan and expected impact
FAQ

Frequent questions

Depends on scope. A simple workflow starts at a couple of days. On a call I'll scope timeline and budget for your case.

Ready to automate the grind?

Drop your contact — I'll reply with ideas you can automate right now.

Reply within 24hNDA on requestFirst audit is free

No spam. Straight to the point.