Too many tools
Work spreads across overlapping systems. Switching between them eats the day.
AI becomes useful when it knows a specific business. Before that, it just speaks in generalities.
Misha Bei
I help businesses reduce operational chaos with AI and digital systems.
15 years in digital, marketing, and operations. Hospitality and investment real estate in Southeast Asia.
What I work with
It holds together because people know how each piece works.
That is how it goes in almost any company growing faster than its processes.
Messy workflows
Handoffs live in chat threads, spreadsheets, and someone's memory. Every step is propped up by hand.
Knowledge trapped in people's heads
Edge cases and working rules are written down nowhere. Without those people the process stops.
Fragmented digital operations
Finance, sales, and operational data each in their own system. No single picture across them.
Flashy AI products that promise to fix everything
Great in the demo and in the deck. Doesn't stick in practice.
What I do
Four areas where I'm most useful.
Digital infrastructure
Websites, booking, CRM, data, distribution. One coherent layer instead of five disconnected ones.
Marketing and sales
Funnels, acquisition, conversion, marketing systems. 15 years in digital, marketing, and data, before AI became useful.
Operational systems
Internal tools, automation, knowledge workflows. Fewer tasks that break when someone is on leave.
AI layer that knows the business
AI draws on company documents, policies, and vocabulary. Built into daily processes, with no separate system alongside.
How I think
What I believe.
AI arrived as a layer on top of what already worked.
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Business knowledge is documents, policies, vocabulary, and real examples of how decisions got made. As long as it lives only in people's heads, AI has nothing to work with.
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Without that, AI produces polished text that only looks like work. It clutters chats, reports, and instructions, and roams through handoffs.
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AI amplifies people who already know the work. For those who don't, it just makes weak work look acceptable.
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An AI tool that sticks is one the team uses daily, like email and calendar. Everything else lives only in the pitch deck.
Where I'm most useful
Manual operations eat revenue and the team's energy.
Different industries, the same problems.
Hospitality
Direct vs OTA sales, staff turnover, guest experience fragmenting across shifts, revenue management flying blind.
Investment real estate developers
Sales pipeline and CRM live in three separate systems, customers handed over to service by hand after the sale, property data in Google Sheets, summaries assembled manually.
Other owner-operator businesses
The owner is stuck in operations. Decisions made by gut feel. Processes are nowhere written down. Digital tools cobbled together from random services and Google Sheets.
Process
How the work happens.
- Audit Which processes are broken, what data already exists, where AI will actually help.
- Architecture Minimum new systems. Maximum integration with what already exists.
- Build I do the work myself, from structure to production code. No chain of subcontractors.
- Rollout Gradual transition. Old and new processes run in parallel until the switch is clean.
- Support I stay in the project after launch for adjustments and tuning.
Talk
Get in touch.
Open to the right in-house, fractional, or project-based conversations.