Mykola Vorobiov

Your domain expertise + one engineer → production system.

No dev team. No specs. No six-month timeline.

Senior Python Developer & System Architect

I don't ask domain experts how the software should work — that overconstrains the problem. I ask what makes the result good, then find an architecture that delivers it.

Currently in production operating
457+sources scraped
30+microservices in production
1 millionpages a day
99.9%uptime
ZeroDevOps team
First paying client at three months. A working system in two. A beta in one.
Book twenty minutes See the systems
Systems

Five production systems across five unrelated industries.

Schematic — shape only

Each built solo by extracting tacit knowledge from domain experts and making it computable. One method, one engineer, repeated proof of transfer.

The five systems, in the knowledge graph's own order — SignalsAPI (recruitment), Virtual BDR (sales), KIMA (real estate), Ush (executive scheduling), a research knowledge platform (scientific research) — each with the tacit knowledge it was built from, the shape it was made computable as, and the industry it serves.

SignalsAPI Recruitment
457+sources fetch w1 fetch w2 fetch wN normalise+ dedupe classify vector store API

Tacit knowledge“How to find good leads”

Scraping and classification pipeline.

Virtual BDR Sales
personaconfig research message sequence interchangeable orchestrator LinkedIn email replies loop back

Tacit knowledge“How to work a prospect”

Composable outreach modules.

KIMA Real estate
agent UI command queue handler A handler B event bus deal projection audit log

Tacit knowledge“How to manage deals in a CRM”

Event and command queue orchestration.

Ush Executive scheduling
calendars travel + rooms stated habits weights w1 .. wN tuned, not fixed scorer slot 1 slot 2 slot 3 ranked, with reasons

Tacit knowledge“How to pick the right meeting slot”

Weighted constraint optimization.

A research knowledge platform Scientific research
papers+ internal docs parse / chunk extract entities+ relations knowledge graph query layer researchers agents

Tacit knowledge“What we know about this domain”

Knowledge graphs for AI.

Two consulting engagements, on someone else's platform, are kept separate from the systems above, which were built solo: an enterprise HR-analytics platform, and a US personal-injury legal-tech platform. What that fence means.

Terms

I replace the team, I don't manage one.

Scoped · monthly · cancellable

Engagements are scoped, with an end date and acceptance criteria. Monthly and cancellable, company to company.

Read both fit lists before you book — the second one is the one that saves us both a call.

Twenty minutes, and you'll know if this is a fit.

Scoped, with an end date and acceptance criteria. Monthly and cancellable, company to company.

Book twenty minutes

Prefer to write first? Mail goes directly to [email protected].